From 4fcc401f717e79a59b3973f26307f468268e2b8c Mon Sep 17 00:00:00 2001
From: "github-classroom[bot]"
 <66690702+github-classroom[bot]@users.noreply.github.com>
Date: Sat, 24 Feb 2024 23:34:39 +0000
Subject: [PATCH 1/4] Setting up GitHub Classroom Feedback


From a39beb6ff1674e8df158fbb6de69323f52af364f Mon Sep 17 00:00:00 2001
From: CostanzoJa <161173618+CostanzoJa@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:52:56 -0600
Subject: [PATCH 2/4] Update editme.md

---
 editme.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/editme.md b/editme.md
index f8fa35c..6cea76b 100644
--- a/editme.md
+++ b/editme.md
@@ -1,3 +1,3 @@
 _Write a question for your teacher below._
 
-Q: 
+Q: What is the color of the sky? 

From dfe002ac8f47fc9c3b4778f9b39ee227f00348c6 Mon Sep 17 00:00:00 2001
From: CostanzoJa <161173618+CostanzoJa@users.noreply.github.com>
Date: Sat, 24 Feb 2024 18:00:42 -0600
Subject: [PATCH 3/4] Update quiz.md

---
 quiz.md | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/quiz.md b/quiz.md
index 430c2d8..d168f91 100644
--- a/quiz.md
+++ b/quiz.md
@@ -15,7 +15,7 @@ Q1. Which statement about GitHub Classroom is true?
 3. GitHub Classroom is a website that provides online courses to learn about GitHub.
 4. GitHub Classroom is developed by 3rd party developers but uses the GitHub API to integrate into GitHub.
 
-Answer:
+Answer: 2
 
 ------
 
@@ -26,7 +26,7 @@ Q2. What does the command `git add` do?
 3. Adds a file to the .git directory
 4. Adds a file to the working directory
 
-Answer:
+Answer: 2
 
 ------
 
@@ -37,7 +37,7 @@ Q3 . What Git commands can be used to correct mistakes?
 3. `git reset` and `git revert`
 4. `git revert` and `git remove`
 
-Answer:
+Answer: 3
 
 ------
 
@@ -48,7 +48,7 @@ Q4. Which GitHub feature provides task automation and workflow functionality, wh
 3. Pull Requests
 4. Actions
 
-Answer:
+Answer: 4
 
 ------
 
@@ -59,4 +59,4 @@ Q5. Pull requests provide a mechanism to request which git action?
 3. merge
 4. push
 
-Answer:
+Answer: 3

From b282fda154672db8b358c02f5035ac56b743572c Mon Sep 17 00:00:00 2001
From: CostanzoJa <161173618+CostanzoJa@users.noreply.github.com>
Date: Mon, 25 Mar 2024 14:24:56 -0500
Subject: [PATCH 4/4] Created using Colaboratory

---
 doseResponse_Assignment.ipynb | 4740 +++++++++++++++++++++++++++++++++
 1 file changed, 4740 insertions(+)
 create mode 100644 doseResponse_Assignment.ipynb

diff --git a/doseResponse_Assignment.ipynb b/doseResponse_Assignment.ipynb
new file mode 100644
index 0000000..bc3c9be
--- /dev/null
+++ b/doseResponse_Assignment.ipynb
@@ -0,0 +1,4740 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/VU-CSP/github-classroom-intro-CostanzoJa/blob/main/doseResponse_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mPYU3pRE6j5s"
+      },
+      "source": [
+        "# Dose–Response Relationships  \n",
+        "\n",
+        "You will need to edit the file Quiz.md to get autograded for this assignment.  \n",
+        "\n",
+        "The first part of the assignment will have you performing analysis on Vanderbilt's Thunor instance.  \n",
+        "\n",
+        "You can access the plots for afatinib treatment using DIP rate or viability at 72 h by following [this link](https://thunor.app.vanderbilt.edu/plots?dataset=13&colsLg=3&colsMd=2&plotdata=plotType%3Ddrc%26datasetId%3D13%26dataset2Id%3D%26useCellLineTags%3Doff%26c%3D8%26c%3D9%26c%3D10%26c%3D11%26c%3D12%26c%3D17%26c%3D18%26useDrugTags%3Doff%26d%3D5%26colorBy%3Doff%26drMetric%3Ddip%26drcType%3Drel&plotdata=plotType%3Ddrc%26datasetId%3D13%26dataset2Id%3D%26useCellLineTags%3Doff%26c%3D8%26c%3D9%26c%3D10%26c%3D11%26c%3D12%26c%3D17%26c%3D18%26useDrugTags%3Doff%26d%3D5%26colorBy%3Doff%26drMetric%3Dviability%26drcType%3Drel)  \n",
+        "\n",
+        "Then you can add new plots as needed to answer the questions in the Quiz.md. You must modify the Quiz.md file to get your grade (either modify the file directly on GitHub or upload to your assignment repository.)  \n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "--7S3yToJ858"
+      },
+      "source": [
+        "You can learn more about Thunor web and how to use it in [this tutorial](https://youtu.be/q4LQCjuBnmg).  \n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "rk7tOb4O6j5t"
+      },
+      "source": [
+        "## Assignment\n",
+        "\n",
+        "Task 1)\n",
+        "Got to [thunor.app.vanderbilt.edu](https://thunor.app.vanderbilt.edu/plots?dataset=13&colsLg=3&colsMd=2&plotdata=plotType%3Ddrc%26datasetId%3D13%26dataset2Id%3D%26useCellLineTags%3Doff%26c%3D8%26c%3D9%26c%3D10%26c%3D11%26c%3D12%26c%3D17%26c%3D18%26useDrugTags%3Doff%26d%3D5%26colorBy%3Doff%26drMetric%3Ddip%26drcType%3Drel&plotdata=plotType%3Ddrc%26datasetId%3D13%26dataset2Id%3D%26useCellLineTags%3Doff%26c%3D8%26c%3D9%26c%3D10%26c%3D11%26c%3D12%26c%3D17%26c%3D18%26useDrugTags%3Doff%26d%3D5%26colorBy%3Doff%26drMetric%3Dviability%26drcType%3Drel) and compare the responses of all cell lines to afatinib using DIP rate or 72 h viability as the effect metric.\n",
+        "\n",
+        "Task 2) Complete all tasks within this notebook  \n",
+        "\n",
+        "Task 3) Edit and submit the Quiz.md file in your assigment repository (you will need to refer to thunor@VU and this notebook).  "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "khJP1y9J-PFx",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "14659d5e-b3d2-4f1d-fa6f-444098a9356f"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting thunor\n",
+            "  Downloading thunor-0.1.30-py3-none-any.whl (58 kB)\n",
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/58.9 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━\u001b[0m \u001b[32m51.2/58.9 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.9/58.9 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from thunor) (1.25.2)\n",
+            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from thunor) (1.11.4)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from thunor) (1.5.3)\n",
+            "Requirement already satisfied: plotly in /usr/local/lib/python3.10/dist-packages (from thunor) (5.15.0)\n",
+            "Requirement already satisfied: seaborn in /usr/local/lib/python3.10/dist-packages (from thunor) (0.13.1)\n",
+            "Requirement already satisfied: tables in /usr/local/lib/python3.10/dist-packages (from thunor) (3.8.0)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->thunor) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->thunor) (2023.4)\n",
+            "Requirement already satisfied: tenacity>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from plotly->thunor) (8.2.3)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from plotly->thunor) (24.0)\n",
+            "Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in /usr/local/lib/python3.10/dist-packages (from seaborn->thunor) (3.7.1)\n",
+            "Requirement already satisfied: cython>=0.29.21 in /usr/local/lib/python3.10/dist-packages (from tables->thunor) (3.0.9)\n",
+            "Requirement already satisfied: numexpr>=2.6.2 in /usr/local/lib/python3.10/dist-packages (from tables->thunor) (2.9.0)\n",
+            "Requirement already satisfied: blosc2~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from tables->thunor) (2.0.0)\n",
+            "Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.10/dist-packages (from tables->thunor) (9.0.0)\n",
+            "Requirement already satisfied: msgpack in /usr/local/lib/python3.10/dist-packages (from blosc2~=2.0.0->tables->thunor) (1.0.8)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn->thunor) (1.2.0)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn->thunor) (0.12.1)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn->thunor) (4.50.0)\n",
+            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn->thunor) (1.4.5)\n",
+            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn->thunor) (9.4.0)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn->thunor) (3.1.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->thunor) (1.16.0)\n",
+            "Installing collected packages: thunor\n",
+            "Successfully installed thunor-0.1.30\n"
+          ]
+        }
+      ],
+      "source": [
+        "try:\n",
+        "  import google.colab\n",
+        "  IN_COLAB = True\n",
+        "except:\n",
+        "  IN_COLAB = False\n",
+        "\n",
+        "if IN_COLAB:\n",
+        "    try:\n",
+        "        import thunor\n",
+        "    except:\n",
+        "        !pip install thunor"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "S7arIb5p6j5v"
+      },
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import scipy.optimize as opt\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "import thunor\n",
+        "from thunor.io import read_hdf\n",
+        "from thunor.dip import dip_rates\n",
+        "from thunor.curve_fit import fit_params\n",
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OEqLRV9i6j5v"
+      },
+      "source": [
+        "#### Define model functions"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "xLwsKFPX6j5v"
+      },
+      "outputs": [],
+      "source": [
+        "def ll4(x,h,E0,Emax,EC50):\n",
+        "    '''\n",
+        "    Reformulation of the LL4 function\n",
+        "     - h: Hill coefficient\n",
+        "     - E0: no-drug effect\n",
+        "     - Emax: max effect\n",
+        "     - EC50: Concentration at midpoint between E0 and Emax\n",
+        "     '''\n",
+        "    return(Emax + (E0-Emax) / (1+np.exp(h*(np.log(x/EC50)))) )\n",
+        "\n",
+        "def ll3(x,b,d,e):\n",
+        "    '''\n",
+        "    3-parameter log-logistic function with no/minimal effect set to a value of 1\n",
+        "     - b: Hill coefficient\n",
+        "     - d: Emax\n",
+        "     - e: EC50\n",
+        "     '''\n",
+        "    return(d + (1-d) / ( 1+np.exp( b*np.log(x/e)) ) )"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "rsr7s8lF6j5w"
+      },
+      "source": [
+        "#### Load all PC9 data using Thunor"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "id": "XNV4lefh6j5w",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "9fa30be8-e239-4e02-82de-59bb03f386b3"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2024-03-25 18:49:27--  https://github.com/VU-CSP/quantbio-assignments/raw/main/data/HTS001.h5\n",
+            "Resolving github.com (github.com)... 140.82.121.3\n",
+            "Connecting to github.com (github.com)|140.82.121.3|:443... connected.\n",
+            "HTTP request sent, awaiting response... 302 Found\n",
+            "Location: https://raw.githubusercontent.com/VU-CSP/quantbio-assignments/main/data/HTS001.h5 [following]\n",
+            "--2024-03-25 18:49:28--  https://raw.githubusercontent.com/VU-CSP/quantbio-assignments/main/data/HTS001.h5\n",
+            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.109.133, ...\n",
+            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 1285259 (1.2M) [application/octet-stream]\n",
+            "Saving to: ‘./data/HTS001.h5’\n",
+            "\n",
+            "./data/HTS001.h5    100%[===================>]   1.23M  --.-KB/s    in 0.02s   \n",
+            "\n",
+            "2024-03-25 18:49:28 (56.2 MB/s) - ‘./data/HTS001.h5’ saved [1285259/1285259]\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "if IN_COLAB and not os.path.exists(\"./data/HTS001.h5\"):\n",
+        "    if not os.path.exists(\"./data\"):\n",
+        "        !mkdir data\n",
+        "    !wget -O ./data/HTS001.h5 https://github.com/VU-CSP/quantbio-assignments/raw/main/data/HTS001.h5\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "4vfqV7ej_u4G"
+      },
+      "source": [
+        "#### Description of HTS001.h5 dataset  \n",
+        "\n",
+        "* PC9 lung adenocarcinoma cell line and six PC9 variants, each treated with 14 different drugs\n",
+        "* All cell lines were genetically modified to express a nuclear-localized fluorescent protein (H2BmRFP) and assessed by live-cell fluorescence microscopy in multiwell plates\n",
+        "* No cell death indicator was used in these experiments (i.e., some of the cell counts may be of dead cells that retained fluorescent nuclear signal)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "AGPMg7hx_veF",
+        "outputId": "605aa977-4eb7-4a7c-d996-796495a9f440"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "HTS Dataset (14 drugs/combos, 7 cell lines)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 5
+        }
+      ],
+      "source": [
+        "hts001 = read_hdf(\"./data/HTS001.h5\")\n",
+        "hts001"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lD-ZAmZG6j5x"
+      },
+      "source": [
+        "### Calculate DIP rates and fit parameters for all conditions using Thunor"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Pg6FhXEpu3R9",
+        "outputId": "3b9cde74-d4aa-4442-e3c5-caab4e458d80"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/thunor/curve_fit.py:157: RuntimeWarning: invalid value encountered in log\n",
+            "  return c + (d - c) / (1 + np.exp(b * (np.log(x) - np.log(e))))\n",
+            "/usr/local/lib/python3.10/dist-packages/thunor/curve_fit.py:224: RuntimeWarning: invalid value encountered in scalar power\n",
+            "  icN = self.ec50 * (ic_frac / (1 - ic_frac - (emax / e0))) ** (\n"
+          ]
+        }
+      ],
+      "source": [
+        "ctrl_diprates, expt_diprates = dip_rates(hts001)\n",
+        "fit_p = fit_params(ctrl_diprates, expt_diprates)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "uplmof9Tv0ck"
+      },
+      "source": [
+        "### Examine the fit parameters using `head()`"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 605
+        },
+        "id": "JUbfwkyCv2bV",
+        "outputId": "7e7ccf6c-bdcf-4bba-df7f-94a553c6ed92"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                                        dip_ctrl  \\\n",
+              "dataset_id cell_line drug                                                          \n",
+              "13         BR1       afatinib  dose          well_id\n",
+              "1.868750e-12  54148     ...   \n",
+              "           DS3       afatinib  dose          well_id\n",
+              "1.868750e-12  54456     ...   \n",
+              "           DS7       afatinib  dose          well_id\n",
+              "1.868750e-12  54764     ...   \n",
+              "           DS8       afatinib  dose          well_id\n",
+              "1.868750e-12  55072     ...   \n",
+              "           DS9       afatinib  dose          well_id\n",
+              "1.868750e-12  55380     ...   \n",
+              "\n",
+              "                                                                        dip_expt  \\\n",
+              "dataset_id cell_line drug                                                          \n",
+              "13         BR1       afatinib  dose          well_id\n",
+              "1.868750e-11  53868     ...   \n",
+              "           DS3       afatinib  dose          well_id\n",
+              "1.868750e-11  54176     ...   \n",
+              "           DS7       afatinib  dose          well_id\n",
+              "1.868750e-11  54484     ...   \n",
+              "           DS8       afatinib  dose          well_id\n",
+              "1.868750e-11  54792     ...   \n",
+              "           DS9       afatinib  dose          well_id\n",
+              "1.868750e-11  55100     ...   \n",
+              "\n",
+              "                                                                         fit_obj  \\\n",
+              "dataset_id cell_line drug                                                          \n",
+              "13         BR1       afatinib  <thunor.curve_fit.HillCurveLL4 object at 0x7f0...   \n",
+              "           DS3       afatinib  <thunor.curve_fit.HillCurveLL4 object at 0x7f0...   \n",
+              "           DS7       afatinib  <thunor.curve_fit.HillCurveLL4 object at 0x7f0...   \n",
+              "           DS8       afatinib  <thunor.curve_fit.HillCurveLL4 object at 0x7f0...   \n",
+              "           DS9       afatinib  <thunor.curve_fit.HillCurveLL4 object at 0x7f0...   \n",
+              "\n",
+              "                               min_dose_measured  max_dose_measured  emax_obs  \\\n",
+              "dataset_id cell_line drug                                                       \n",
+              "13         BR1       afatinib       1.868750e-12           0.000004 -0.016577   \n",
+              "           DS3       afatinib       1.868750e-12           0.000004 -0.011857   \n",
+              "           DS7       afatinib       1.868750e-12           0.000004 -0.015582   \n",
+              "           DS8       afatinib       1.868750e-12           0.000004 -0.011272   \n",
+              "           DS9       afatinib       1.868750e-12           0.000004 -0.011257   \n",
+              "\n",
+              "                                 aa_obs          label          ic50  \\\n",
+              "dataset_id cell_line drug                                              \n",
+              "13         BR1       afatinib  1.512939  BR1\\nafatinib  3.006719e-07   \n",
+              "           DS3       afatinib  5.548105  DS3\\nafatinib  3.034130e-11   \n",
+              "           DS7       afatinib  4.355910  DS7\\nafatinib  5.993042e-11   \n",
+              "           DS8       afatinib  3.708655  DS8\\nafatinib  9.443298e-11   \n",
+              "           DS9       afatinib  4.820104  DS9\\nafatinib  4.533335e-11   \n",
+              "\n",
+              "                                       ec50      emax       einf  emax_rel  \\\n",
+              "dataset_id cell_line drug                                                    \n",
+              "13         BR1       afatinib  3.968750e-06 -0.007034 -22.244175 -0.221182   \n",
+              "           DS3       afatinib  3.630411e-11 -0.004809  -0.004809 -0.139991   \n",
+              "           DS7       afatinib  5.188016e-11  0.004615   0.004615  0.118395   \n",
+              "           DS8       afatinib  7.862445e-11  0.006191   0.006191  0.154127   \n",
+              "           DS9       afatinib  4.868199e-11 -0.002011  -0.002011 -0.055564   \n",
+              "\n",
+              "                               emax_obs_rel        aa           auc      hill  \n",
+              "dataset_id cell_line drug                                                      \n",
+              "13         BR1       afatinib     -0.521250  1.522150  10006.926303  0.346485  \n",
+              "           DS3       afatinib     -0.345116  5.738045      1.474794  1.375790  \n",
+              "           DS7       afatinib     -0.399753  4.305049      1.272956  1.873320  \n",
+              "           DS8       afatinib     -0.280602  3.978123      1.373802  2.011579  \n",
+              "           DS9       afatinib     -0.311075  5.181684      1.496975  1.478611  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-8332884f-ceba-41eb-aae1-0ebf1c10366d\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
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+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>dip_ctrl</th>\n",
+              "      <th>dip_expt</th>\n",
+              "      <th>fit_obj</th>\n",
+              "      <th>min_dose_measured</th>\n",
+              "      <th>max_dose_measured</th>\n",
+              "      <th>emax_obs</th>\n",
+              "      <th>aa_obs</th>\n",
+              "      <th>label</th>\n",
+              "      <th>ic50</th>\n",
+              "      <th>ec50</th>\n",
+              "      <th>emax</th>\n",
+              "      <th>einf</th>\n",
+              "      <th>emax_rel</th>\n",
+              "      <th>emax_obs_rel</th>\n",
+              "      <th>aa</th>\n",
+              "      <th>auc</th>\n",
+              "      <th>hill</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>dataset_id</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>drug</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">13</th>\n",
+              "      <th>BR1</th>\n",
+              "      <th>afatinib</th>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-12  54148     ...</td>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-11  53868     ...</td>\n",
+              "      <td>&lt;thunor.curve_fit.HillCurveLL4 object at 0x7f0...</td>\n",
+              "      <td>1.868750e-12</td>\n",
+              "      <td>0.000004</td>\n",
+              "      <td>-0.016577</td>\n",
+              "      <td>1.512939</td>\n",
+              "      <td>BR1\\nafatinib</td>\n",
+              "      <td>3.006719e-07</td>\n",
+              "      <td>3.968750e-06</td>\n",
+              "      <td>-0.007034</td>\n",
+              "      <td>-22.244175</td>\n",
+              "      <td>-0.221182</td>\n",
+              "      <td>-0.521250</td>\n",
+              "      <td>1.522150</td>\n",
+              "      <td>10006.926303</td>\n",
+              "      <td>0.346485</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DS3</th>\n",
+              "      <th>afatinib</th>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-12  54456     ...</td>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-11  54176     ...</td>\n",
+              "      <td>&lt;thunor.curve_fit.HillCurveLL4 object at 0x7f0...</td>\n",
+              "      <td>1.868750e-12</td>\n",
+              "      <td>0.000004</td>\n",
+              "      <td>-0.011857</td>\n",
+              "      <td>5.548105</td>\n",
+              "      <td>DS3\\nafatinib</td>\n",
+              "      <td>3.034130e-11</td>\n",
+              "      <td>3.630411e-11</td>\n",
+              "      <td>-0.004809</td>\n",
+              "      <td>-0.004809</td>\n",
+              "      <td>-0.139991</td>\n",
+              "      <td>-0.345116</td>\n",
+              "      <td>5.738045</td>\n",
+              "      <td>1.474794</td>\n",
+              "      <td>1.375790</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DS7</th>\n",
+              "      <th>afatinib</th>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-12  54764     ...</td>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-11  54484     ...</td>\n",
+              "      <td>&lt;thunor.curve_fit.HillCurveLL4 object at 0x7f0...</td>\n",
+              "      <td>1.868750e-12</td>\n",
+              "      <td>0.000004</td>\n",
+              "      <td>-0.015582</td>\n",
+              "      <td>4.355910</td>\n",
+              "      <td>DS7\\nafatinib</td>\n",
+              "      <td>5.993042e-11</td>\n",
+              "      <td>5.188016e-11</td>\n",
+              "      <td>0.004615</td>\n",
+              "      <td>0.004615</td>\n",
+              "      <td>0.118395</td>\n",
+              "      <td>-0.399753</td>\n",
+              "      <td>4.305049</td>\n",
+              "      <td>1.272956</td>\n",
+              "      <td>1.873320</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DS8</th>\n",
+              "      <th>afatinib</th>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-12  55072     ...</td>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-11  54792     ...</td>\n",
+              "      <td>&lt;thunor.curve_fit.HillCurveLL4 object at 0x7f0...</td>\n",
+              "      <td>1.868750e-12</td>\n",
+              "      <td>0.000004</td>\n",
+              "      <td>-0.011272</td>\n",
+              "      <td>3.708655</td>\n",
+              "      <td>DS8\\nafatinib</td>\n",
+              "      <td>9.443298e-11</td>\n",
+              "      <td>7.862445e-11</td>\n",
+              "      <td>0.006191</td>\n",
+              "      <td>0.006191</td>\n",
+              "      <td>0.154127</td>\n",
+              "      <td>-0.280602</td>\n",
+              "      <td>3.978123</td>\n",
+              "      <td>1.373802</td>\n",
+              "      <td>2.011579</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>DS9</th>\n",
+              "      <th>afatinib</th>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-12  55380     ...</td>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-11  55100     ...</td>\n",
+              "      <td>&lt;thunor.curve_fit.HillCurveLL4 object at 0x7f0...</td>\n",
+              "      <td>1.868750e-12</td>\n",
+              "      <td>0.000004</td>\n",
+              "      <td>-0.011257</td>\n",
+              "      <td>4.820104</td>\n",
+              "      <td>DS9\\nafatinib</td>\n",
+              "      <td>4.533335e-11</td>\n",
+              "      <td>4.868199e-11</td>\n",
+              "      <td>-0.002011</td>\n",
+              "      <td>-0.002011</td>\n",
+              "      <td>-0.055564</td>\n",
+              "      <td>-0.311075</td>\n",
+              "      <td>5.181684</td>\n",
+              "      <td>1.496975</td>\n",
+              "      <td>1.478611</td>\n",
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+              "      fill: #D2E3FC;\n",
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+              "\n",
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+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
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+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
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+              "\n",
+              "  <script>\n",
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+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
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+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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+            ],
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+              "type": "dataframe",
+              "variable_name": "fit_p",
+              "summary": "{\n  \"name\": \"fit_p\",\n  \"rows\": 98,\n  \"fields\": [\n    {\n      \"column\": \"dip_ctrl\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_expt\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fit_obj\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 83,\n        \"samples\": [\n          \"<thunor.curve_fit.HillCurveLL4 object at 0x7f077fc82c80>\",\n          \"<thunor.curve_fit.HillCurveLL4 object at 0x7f077fc91300>\",\n          \"<thunor.curve_fit.HillCurveLL4 object at 0x7f077fc90790>\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"min_dose_measured\",\n      \"properties\": {\n        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\"column\": \"emax\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.012706732764218315,\n        \"min\": -0.012624118056806018,\n        \"max\": 0.04630499475260278,\n        \"num_unique_values\": 83,\n        \"samples\": [\n          0.011611297875329774,\n          -0.007034182826007651,\n          0.008491989704703246\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"einf\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.795832578252673,\n        \"min\": -33.788183477543285,\n        \"max\": 0.04630499475260278,\n        \"num_unique_values\": 83,\n        \"samples\": [\n          0.011611297564579442,\n          -22.244174752423355,\n          0.00849191031792347\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"emax_rel\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.33846635603598324,\n        \"min\": -0.3934884243412534,\n        \"max\": 1.0,\n        \"num_unique_values\": 79,\n        \"samples\": [\n          0.24708681775191946,\n          -0.2211819278227472,\n          0.21127878438139966\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"emax_obs_rel\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.38378013190083216,\n        \"min\": -1.112971152583923,\n        \"max\": 0.9187687703721477,\n        \"num_unique_values\": 83,\n        \"samples\": [\n          0.16507944367221383,\n          -0.5212496628238175,\n          0.12161589028504526\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"aa\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.1197018156659857,\n        \"min\": 0.0,\n        \"max\": 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       0.34648546195652563,\n          10.96177888796202\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 7
+        }
+      ],
+      "source": [
+        "fit_p.head()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "E0_0fUk_X_9X"
+      },
+      "source": [
+        "### Download DIP rate data (automatically fit to time course data by Thunor)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 403
+        },
+        "id": "92FYfjGFP9ev",
+        "outputId": "fa528e79-062a-4f65-8f2a-6754a36b80b6"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2024-03-25 18:49:57--  https://thunor.app.vanderbilt.edu/dataset/13/download/dip_rates\n",
+            "Resolving thunor.app.vanderbilt.edu (thunor.app.vanderbilt.edu)... 52.202.96.219, 3.219.141.193, 3.224.136.119, ...\n",
+            "Connecting to thunor.app.vanderbilt.edu (thunor.app.vanderbilt.edu)|52.202.96.219|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 173629 (170K) [text/tab-separated-values]\n",
+            "Saving to: ‘./data/hts001_diprates.tsv’\n",
+            "\n",
+            "./data/hts001_dipra 100%[===================>] 169.56K   861KB/s    in 0.2s    \n",
+            "\n",
+            "2024-03-25 18:49:58 (861 KB/s) - ‘./data/hts001_diprates.tsv’ saved [173629/173629]\n",
+            "\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "          plate well cell_line       drug          conc  dip_rate  \\\n",
+              "0  HTS001_BR1-2   B2       BR1        NaN           NaN  0.033001   \n",
+              "1  HTS001_BR1-2   B3       BR1  erlotinib  3.968750e-06  0.024479   \n",
+              "2  HTS001_BR1-2   B4       BR1  erlotinib  9.921250e-07  0.028890   \n",
+              "3  HTS001_BR1-2   B5       BR1  erlotinib  2.480000e-07  0.029436   \n",
+              "4  HTS001_BR1-2   B6       BR1  erlotinib  6.201250e-08  0.024072   \n",
+              "\n",
+              "   dip_fit_std_err  \n",
+              "0         0.001192  \n",
+              "1         0.000853  \n",
+              "2         0.001007  \n",
+              "3         0.001091  \n",
+              "4         0.000832  "
+            ],
+            "text/html": [
+              "\n",
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+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
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+              "\n",
+              "    .dataframe thead th {\n",
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+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>plate</th>\n",
+              "      <th>well</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>drug</th>\n",
+              "      <th>conc</th>\n",
+              "      <th>dip_rate</th>\n",
+              "      <th>dip_fit_std_err</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.033001</td>\n",
+              "      <td>0.001192</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B3</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>erlotinib</td>\n",
+              "      <td>3.968750e-06</td>\n",
+              "      <td>0.024479</td>\n",
+              "      <td>0.000853</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>erlotinib</td>\n",
+              "      <td>9.921250e-07</td>\n",
+              "      <td>0.028890</td>\n",
+              "      <td>0.001007</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B5</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>erlotinib</td>\n",
+              "      <td>2.480000e-07</td>\n",
+              "      <td>0.029436</td>\n",
+              "      <td>0.001091</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B6</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>erlotinib</td>\n",
+              "      <td>6.201250e-08</td>\n",
+              "      <td>0.024072</td>\n",
+              "      <td>0.000832</td>\n",
+              "    </tr>\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
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+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
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+              "        document.querySelector('#df-ca52a5f2-0d8f-4e04-b45d-11a360f6a727 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-ca52a5f2-0d8f-4e04-b45d-11a360f6a727');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
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+              "\n",
+              "\n",
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+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-26a1b8ce-cd8d-47a3-8c0f-29975320d1f0')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
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+              "     width=\"24px\">\n",
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+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
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+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
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+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-26a1b8ce-cd8d-47a3-8c0f-29975320d1f0 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "hts001_diprates",
+              "summary": "{\n  \"name\": \"hts001_diprates\",\n  \"rows\": 2156,\n  \"fields\": [\n    {\n      \"column\": \"plate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"HTS001_BR1-2\",\n          \"HTS001_DS3-2\",\n          \"HTS001_MGH-2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"well\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 308,\n        \"samples\": [\n          \"O4\",\n          \"B11\",\n          \"D15\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cell_line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"BR1\",\n          \"DS3\",\n          \"MGH\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"drug\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 14,\n        \"samples\": [\n          \"dactolisib\",\n          \"paclitaxel\",\n          \"erlotinib\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"conc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.0758656609662284e-06,\n        \"min\": 1.86875e-12,\n        \"max\": 3.96875e-06,\n        \"num_unique_values\": 30,\n        \"samples\": [\n          1.52625e-10,\n          3.72e-10,\n          3.100625e-08\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.01602631166571511,\n        \"min\": -0.0357069696460849,\n        \"max\": 0.0561220180132467,\n        \"num_unique_values\": 2156,\n        \"samples\": [\n          0.0125726426927411,\n          0.0359265856833508,\n          0.0080518821198872\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_fit_std_err\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0005985166638877234,\n        \"min\": 0.000202023565259,\n        \"max\": 0.0087252198583607,\n        \"num_unique_values\": 2156,\n        \"samples\": [\n          0.0005080237318882,\n          0.0004023821310002,\n          0.001055365859999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 8
+        }
+      ],
+      "source": [
+        "if not os.path.exists(\"./data/hts001_diprates.tsv\"):\n",
+        "    !wget -O \"./data/hts001_diprates.tsv\" https://thunor.app.vanderbilt.edu/dataset/13/download/dip_rates\n",
+        "\n",
+        "hts001_diprates = pd.read_csv(\"./data/hts001_diprates.tsv\", sep='\\t')\n",
+        "hts001_diprates.rename(columns={'cell.line': 'cell_line', 'drug1':'drug', 'drug1.conc':'conc'}, inplace=True)\n",
+        "hts001_diprates.head()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "cxSLbyxaPyIP"
+      },
+      "source": [
+        "### Extract only cell count data from afatinib treatment\n",
+        "Start from full dataset (`hts001`)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IoZn209SQEdI",
+        "outputId": "9e01b17f-424d-464d-83ad-77e2b0754f19"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "HTS Dataset (1 drugs/combos, 7 cell lines)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 9
+        }
+      ],
+      "source": [
+        "afat = hts001.filter(drugs=['afatinib'])\n",
+        "afat"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BVr5Fnj-Y2J_"
+      },
+      "source": [
+        "### Load thunor plotting functions"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {
+        "id": "2Jh8ZomUQtDb"
+      },
+      "outputs": [],
+      "source": [
+        "from thunor.plots import plot_drc, plot_drc_params, plot_time_course, plot_ctrl_dip_by_plate, plot_plate_map\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "bN48jA7dYcDY"
+      },
+      "source": [
+        "### Filter fit parameters for all cell lines treated with afatinib, and plot dose–response curves"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 417
+        },
+        "id": "rci_WQEttrZd",
+        "outputId": "21ea8be5-8521-4736-dafc-99d04ef34bf6"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
+              "<html>\n",
+              "<head><meta charset=\"utf-8\" /></head>\n",
+              "<body>\n",
+              "    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
+              "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-2.24.1.min.js\"></script>                <div id=\"cbf09908-9075-461b-8417-4fa31f4494ce\" class=\"plotly-graph-div\" style=\"height:400px; width:400px;\"></div>            <script type=\"text/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"cbf09908-9075-461b-8417-4fa31f4494ce\")) {                    Plotly.newPlot(                        \"cbf09908-9075-461b-8417-4fa31f4494ce\",                        [{\"hoverinfo\":\"all\",\"legendgroup\":\"BR1\\nafatinib\",\"line\":{\"color\":\"rgb(244, 93, 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+              "// Listen for the clearing of the current output cell\n",
+              "var outputEl = gd.closest('.output');\n",
+              "if (outputEl) {{\n",
+              "    x.observe(outputEl, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "                        })                };                            </script>        </div>\n",
+              "</body>\n",
+              "</html>"
+            ]
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "fit_p_afat = fit_p[fit_p.index.isin(['afatinib'], level='drug')]\n",
+        "fig = plot_drc(fit_p_afat)\n",
+        "fig.update_layout(\n",
+        "    autosize=False,\n",
+        "    width=400,\n",
+        "    height=400,)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-dmfJorfZD3N"
+      },
+      "source": [
+        "### Filter fit parameters by cell line (`BR1`) and drug (`paclitaxel`)\n",
+        "and display result"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        },
+        "id": "exubzfztuLpd",
+        "outputId": "ad5afaa8-65be-49f6-843f-1cb805eca4c8"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                                          dip_ctrl  \\\n",
+              "dataset_id cell_line drug                                                            \n",
+              "13         BR1       paclitaxel  dose          well_id\n",
+              "1.868750e-12  54148     ...   \n",
+              "\n",
+              "                                                                          dip_expt  \\\n",
+              "dataset_id cell_line drug                                                            \n",
+              "13         BR1       paclitaxel  dose          well_id\n",
+              "1.868750e-11  54028     ...   \n",
+              "\n",
+              "                                fit_obj  min_dose_measured  max_dose_measured  \\\n",
+              "dataset_id cell_line drug                                                       \n",
+              "13         BR1       paclitaxel    None       1.868750e-12           0.000004   \n",
+              "\n",
+              "                                 emax_obs    aa_obs            label  ic50  \\\n",
+              "dataset_id cell_line drug                                                    \n",
+              "13         BR1       paclitaxel -0.025586  4.509109  BR1\\npaclitaxel   NaN   \n",
+              "\n",
+              "                                 ec50  emax  einf  emax_rel  emax_obs_rel  aa  \\\n",
+              "dataset_id cell_line drug                                                       \n",
+              "13         BR1       paclitaxel   NaN   NaN   NaN       NaN           NaN NaN   \n",
+              "\n",
+              "                                 auc  hill  \n",
+              "dataset_id cell_line drug                   \n",
+              "13         BR1       paclitaxel  NaN   NaN  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-ced65ef8-e07f-480b-bf88-2f0a1489766a\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>dip_ctrl</th>\n",
+              "      <th>dip_expt</th>\n",
+              "      <th>fit_obj</th>\n",
+              "      <th>min_dose_measured</th>\n",
+              "      <th>max_dose_measured</th>\n",
+              "      <th>emax_obs</th>\n",
+              "      <th>aa_obs</th>\n",
+              "      <th>label</th>\n",
+              "      <th>ic50</th>\n",
+              "      <th>ec50</th>\n",
+              "      <th>emax</th>\n",
+              "      <th>einf</th>\n",
+              "      <th>emax_rel</th>\n",
+              "      <th>emax_obs_rel</th>\n",
+              "      <th>aa</th>\n",
+              "      <th>auc</th>\n",
+              "      <th>hill</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>dataset_id</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>drug</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <th>BR1</th>\n",
+              "      <th>paclitaxel</th>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-12  54148     ...</td>\n",
+              "      <td>dose          well_id\n",
+              "1.868750e-11  54028     ...</td>\n",
+              "      <td>None</td>\n",
+              "      <td>1.868750e-12</td>\n",
+              "      <td>0.000004</td>\n",
+              "      <td>-0.025586</td>\n",
+              "      <td>4.509109</td>\n",
+              "      <td>BR1\\npaclitaxel</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ced65ef8-e07f-480b-bf88-2f0a1489766a')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-ced65ef8-e07f-480b-bf88-2f0a1489766a button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-ced65ef8-e07f-480b-bf88-2f0a1489766a');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "fp_br1_pacl",
+              "repr_error": "0"
+            }
+          },
+          "metadata": {},
+          "execution_count": 12
+        }
+      ],
+      "source": [
+        "fp_br1_pacl = fit_p[fit_p.index.isin(['BR1'], level='cell_line') & \\\n",
+        "               fit_p.index.isin(['paclitaxel'], level='drug')]\n",
+        "fp_br1_pacl"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "FFJq-8AtO4E1"
+      },
+      "source": [
+        "### Show the result of Thunor-fit DIP rates\n",
+        "Saved in `expt_diprates`"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 455
+        },
+        "id": "EliKZH68CE1Y",
+        "outputId": "00ea7cbf-6e80-4f18-8420-2f1937d489ad"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                        well_num  \\\n",
+              "dataset drug          cell_line dose           well_id             \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868          93   \n",
+              "                                               53869         261   \n",
+              "                                (7.47625e-11,) 53870          92   \n",
+              "                                               53871         260   \n",
+              "                                (3.0525e-10,)  53872          91   \n",
+              "...                                                          ...   \n",
+              "        (trametinib,) PC9       (2.48e-08,)    55991         278   \n",
+              "                                (9.92125e-08,) 55992         109   \n",
+              "                                               55993         277   \n",
+              "                                (3.96875e-07,) 55994         108   \n",
+              "                                               55995         276   \n",
+              "\n",
+              "                                                               plate  \\\n",
+              "dataset drug          cell_line dose           well_id                 \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868    HTS001_BR1-2   \n",
+              "                                               53869    HTS001_BR1-2   \n",
+              "                                (7.47625e-11,) 53870    HTS001_BR1-2   \n",
+              "                                               53871    HTS001_BR1-2   \n",
+              "                                (3.0525e-10,)  53872    HTS001_BR1-2   \n",
+              "...                                                              ...   \n",
+              "        (trametinib,) PC9       (2.48e-08,)    55991    HTS001_PC9-2   \n",
+              "                                (9.92125e-08,) 55992    HTS001_PC9-2   \n",
+              "                                               55993    HTS001_PC9-2   \n",
+              "                                (3.96875e-07,) 55994    HTS001_PC9-2   \n",
+              "                                               55995    HTS001_PC9-2   \n",
+              "\n",
+              "                                                        dip_rate  \\\n",
+              "dataset drug          cell_line dose           well_id             \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868    0.029535   \n",
+              "                                               53869    0.028068   \n",
+              "                                (7.47625e-11,) 53870    0.028230   \n",
+              "                                               53871    0.029678   \n",
+              "                                (3.0525e-10,)  53872    0.029814   \n",
+              "...                                                          ...   \n",
+              "        (trametinib,) PC9       (2.48e-08,)    55991    0.031916   \n",
+              "                                (9.92125e-08,) 55992    0.012482   \n",
+              "                                               55993    0.010134   \n",
+              "                                (3.96875e-07,) 55994    0.013977   \n",
+              "                                               55995    0.012052   \n",
+              "\n",
+              "                                                        dip_fit_std_err  \\\n",
+              "dataset drug          cell_line dose           well_id                    \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868           0.000915   \n",
+              "                                               53869           0.000787   \n",
+              "                                (7.47625e-11,) 53870           0.000882   \n",
+              "                                               53871           0.000935   \n",
+              "                                (3.0525e-10,)  53872           0.001067   \n",
+              "...                                                                 ...   \n",
+              "        (trametinib,) PC9       (2.48e-08,)    55991           0.000954   \n",
+              "                                (9.92125e-08,) 55992           0.001204   \n",
+              "                                               55993           0.001333   \n",
+              "                                (3.96875e-07,) 55994           0.002074   \n",
+              "                                               55995           0.001336   \n",
+              "\n",
+              "                                                        dip_first_timepoint  \\\n",
+              "dataset drug          cell_line dose           well_id                        \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868                   31.1   \n",
+              "                                               53869                   48.5   \n",
+              "                                (7.47625e-11,) 53870                   48.5   \n",
+              "                                               53871                   48.5   \n",
+              "                                (3.0525e-10,)  53872                   51.8   \n",
+              "...                                                                     ...   \n",
+              "        (trametinib,) PC9       (2.48e-08,)    55991                    3.3   \n",
+              "                                (9.92125e-08,) 55992                   46.4   \n",
+              "                                               55993                   59.4   \n",
+              "                                (3.96875e-07,) 55994                   19.0   \n",
+              "                                               55995                   19.0   \n",
+              "\n",
+              "                                                        dip_y_intercept  \n",
+              "dataset drug          cell_line dose           well_id                   \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868           6.269507  \n",
+              "                                               53869           5.714175  \n",
+              "                                (7.47625e-11,) 53870           6.518346  \n",
+              "                                               53871           5.931319  \n",
+              "                                (3.0525e-10,)  53872           6.501894  \n",
+              "...                                                                 ...  \n",
+              "        (trametinib,) PC9       (2.48e-08,)    55991           5.130884  \n",
+              "                                (9.92125e-08,) 55992           6.244496  \n",
+              "                                               55993           6.356689  \n",
+              "                                (3.96875e-07,) 55994           5.819961  \n",
+              "                                               55995           5.663721  \n",
+              "\n",
+              "[1960 rows x 6 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-96a8e039-b57e-446f-bc01-b1d78fce603e\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
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+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
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+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>well_num</th>\n",
+              "      <th>plate</th>\n",
+              "      <th>dip_rate</th>\n",
+              "      <th>dip_fit_std_err</th>\n",
+              "      <th>dip_first_timepoint</th>\n",
+              "      <th>dip_y_intercept</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>dataset</th>\n",
+              "      <th>drug</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>dose</th>\n",
+              "      <th>well_id</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"11\" valign=\"top\">13</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">(afatinib,)</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">BR1</th>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(1.86875e-11,)</th>\n",
+              "      <th>53868</th>\n",
+              "      <td>93</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.029535</td>\n",
+              "      <td>0.000915</td>\n",
+              "      <td>31.1</td>\n",
+              "      <td>6.269507</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>53869</th>\n",
+              "      <td>261</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.028068</td>\n",
+              "      <td>0.000787</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>5.714175</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(7.47625e-11,)</th>\n",
+              "      <th>53870</th>\n",
+              "      <td>92</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.028230</td>\n",
+              "      <td>0.000882</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>6.518346</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>53871</th>\n",
+              "      <td>260</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.029678</td>\n",
+              "      <td>0.000935</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>5.931319</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(3.0525e-10,)</th>\n",
+              "      <th>53872</th>\n",
+              "      <td>91</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.029814</td>\n",
+              "      <td>0.001067</td>\n",
+              "      <td>51.8</td>\n",
+              "      <td>6.501894</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">(trametinib,)</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">PC9</th>\n",
+              "      <th>(2.48e-08,)</th>\n",
+              "      <th>55991</th>\n",
+              "      <td>278</td>\n",
+              "      <td>HTS001_PC9-2</td>\n",
+              "      <td>0.031916</td>\n",
+              "      <td>0.000954</td>\n",
+              "      <td>3.3</td>\n",
+              "      <td>5.130884</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(9.92125e-08,)</th>\n",
+              "      <th>55992</th>\n",
+              "      <td>109</td>\n",
+              "      <td>HTS001_PC9-2</td>\n",
+              "      <td>0.012482</td>\n",
+              "      <td>0.001204</td>\n",
+              "      <td>46.4</td>\n",
+              "      <td>6.244496</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>55993</th>\n",
+              "      <td>277</td>\n",
+              "      <td>HTS001_PC9-2</td>\n",
+              "      <td>0.010134</td>\n",
+              "      <td>0.001333</td>\n",
+              "      <td>59.4</td>\n",
+              "      <td>6.356689</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(3.96875e-07,)</th>\n",
+              "      <th>55994</th>\n",
+              "      <td>108</td>\n",
+              "      <td>HTS001_PC9-2</td>\n",
+              "      <td>0.013977</td>\n",
+              "      <td>0.002074</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>5.819961</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>55995</th>\n",
+              "      <td>276</td>\n",
+              "      <td>HTS001_PC9-2</td>\n",
+              "      <td>0.012052</td>\n",
+              "      <td>0.001336</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>5.663721</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>1960 rows × 6 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-96a8e039-b57e-446f-bc01-b1d78fce603e')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-96a8e039-b57e-446f-bc01-b1d78fce603e button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-96a8e039-b57e-446f-bc01-b1d78fce603e');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-f67f3b39-313c-4255-b5c7-ffc68978f6f4\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f67f3b39-313c-4255-b5c7-ffc68978f6f4')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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+              "    <g>\n",
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+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-f67f3b39-313c-4255-b5c7-ffc68978f6f4 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "expt_diprates",
+              "summary": "{\n  \"name\": \"expt_diprates\",\n  \"rows\": 1960,\n  \"fields\": [\n    {\n      \"column\": \"well_num\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 96,\n        \"min\": 26,\n        \"max\": 357,\n        \"num_unique_values\": 280,\n        \"samples\": [\n          351,\n          79,\n          155\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"plate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"HTS001_BR1-2\",\n          \"HTS001_DS3-2\",\n          \"HTS001_MGH-2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.016234317409122602,\n        \"min\": -0.03570696964608489,\n        \"max\": 0.05612201801324669,\n        \"num_unique_values\": 1960,\n        \"samples\": [\n          0.01210473517595195,\n          0.027183989749331488,\n          0.007200230724481578\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_fit_std_err\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0006034935065403423,\n        \"min\": 0.00020202356525905992,\n        \"max\": 0.008725219858360715,\n        \"num_unique_values\": 1960,\n        \"samples\": [\n          0.002036401957890734,\n          0.0009771864402129038,\n          0.0006784174836285448\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_first_timepoint\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 24.266790853243254,\n        \"min\": 0.5,\n        \"max\": 108.3,\n        \"num_unique_values\": 117,\n        \"samples\": [\n          74.1,\n          73.7,\n          93.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_y_intercept\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.8591871395889485,\n        \"min\": 2.385729022680922,\n        \"max\": 9.827597182648367,\n        \"num_unique_values\": 1960,\n        \"samples\": [\n          5.305195015027132,\n          6.555440354596206,\n          7.932192414302392\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 13
+        }
+      ],
+      "source": [
+        "expt_diprates"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0TaML9g5PHgY"
+      },
+      "source": [
+        "### Filter DIP rates by cell line (`BR1`) and drug (`paclitaxel`)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 455
+        },
+        "id": "Xur3lXkaCcmw",
+        "outputId": "0f0c5a07-4fdf-4eae-a013-471e22d4d661"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                        well_num  \\\n",
+              "dataset drug          cell_line dose           well_id             \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868          93   \n",
+              "                                               53869         261   \n",
+              "                                (7.47625e-11,) 53870          92   \n",
+              "                                               53871         260   \n",
+              "                                (3.0525e-10,)  53872          91   \n",
+              "...                                                          ...   \n",
+              "        (trametinib,) BR1       (2.48e-08,)    54143         278   \n",
+              "                                (9.92125e-08,) 54144         109   \n",
+              "                                               54145         277   \n",
+              "                                (3.96875e-07,) 54146         108   \n",
+              "                                               54147         276   \n",
+              "\n",
+              "                                                               plate  \\\n",
+              "dataset drug          cell_line dose           well_id                 \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868    HTS001_BR1-2   \n",
+              "                                               53869    HTS001_BR1-2   \n",
+              "                                (7.47625e-11,) 53870    HTS001_BR1-2   \n",
+              "                                               53871    HTS001_BR1-2   \n",
+              "                                (3.0525e-10,)  53872    HTS001_BR1-2   \n",
+              "...                                                              ...   \n",
+              "        (trametinib,) BR1       (2.48e-08,)    54143    HTS001_BR1-2   \n",
+              "                                (9.92125e-08,) 54144    HTS001_BR1-2   \n",
+              "                                               54145    HTS001_BR1-2   \n",
+              "                                (3.96875e-07,) 54146    HTS001_BR1-2   \n",
+              "                                               54147    HTS001_BR1-2   \n",
+              "\n",
+              "                                                        dip_rate  \\\n",
+              "dataset drug          cell_line dose           well_id             \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868    0.029535   \n",
+              "                                               53869    0.028068   \n",
+              "                                (7.47625e-11,) 53870    0.028230   \n",
+              "                                               53871    0.029678   \n",
+              "                                (3.0525e-10,)  53872    0.029814   \n",
+              "...                                                          ...   \n",
+              "        (trametinib,) BR1       (2.48e-08,)    54143    0.022501   \n",
+              "                                (9.92125e-08,) 54144    0.011880   \n",
+              "                                               54145    0.016449   \n",
+              "                                (3.96875e-07,) 54146    0.006953   \n",
+              "                                               54147    0.010494   \n",
+              "\n",
+              "                                                        dip_fit_std_err  \\\n",
+              "dataset drug          cell_line dose           well_id                    \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868           0.000915   \n",
+              "                                               53869           0.000787   \n",
+              "                                (7.47625e-11,) 53870           0.000882   \n",
+              "                                               53871           0.000935   \n",
+              "                                (3.0525e-10,)  53872           0.001067   \n",
+              "...                                                                 ...   \n",
+              "        (trametinib,) BR1       (2.48e-08,)    54143           0.000752   \n",
+              "                                (9.92125e-08,) 54144           0.001022   \n",
+              "                                               54145           0.001056   \n",
+              "                                (3.96875e-07,) 54146           0.001200   \n",
+              "                                               54147           0.001388   \n",
+              "\n",
+              "                                                        dip_first_timepoint  \\\n",
+              "dataset drug          cell_line dose           well_id                        \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868                   31.1   \n",
+              "                                               53869                   48.5   \n",
+              "                                (7.47625e-11,) 53870                   48.5   \n",
+              "                                               53871                   48.5   \n",
+              "                                (3.0525e-10,)  53872                   51.8   \n",
+              "...                                                                     ...   \n",
+              "        (trametinib,) BR1       (2.48e-08,)    54143                   55.1   \n",
+              "                                (9.92125e-08,) 54144                   55.1   \n",
+              "                                               54145                   48.5   \n",
+              "                                (3.96875e-07,) 54146                   51.8   \n",
+              "                                               54147                   48.5   \n",
+              "\n",
+              "                                                        dip_y_intercept  \n",
+              "dataset drug          cell_line dose           well_id                   \n",
+              "13      (afatinib,)   BR1       (1.86875e-11,) 53868           6.269507  \n",
+              "                                               53869           5.714175  \n",
+              "                                (7.47625e-11,) 53870           6.518346  \n",
+              "                                               53871           5.931319  \n",
+              "                                (3.0525e-10,)  53872           6.501894  \n",
+              "...                                                                 ...  \n",
+              "        (trametinib,) BR1       (2.48e-08,)    54143           6.505787  \n",
+              "                                (9.92125e-08,) 54144           7.732698  \n",
+              "                                               54145           6.951063  \n",
+              "                                (3.96875e-07,) 54146           7.678181  \n",
+              "                                               54147           6.785053  \n",
+              "\n",
+              "[280 rows x 6 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-8f52d40d-211a-41fc-af89-a909d36b8103\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
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+              "\n",
+              "    .dataframe thead th {\n",
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+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>well_num</th>\n",
+              "      <th>plate</th>\n",
+              "      <th>dip_rate</th>\n",
+              "      <th>dip_fit_std_err</th>\n",
+              "      <th>dip_first_timepoint</th>\n",
+              "      <th>dip_y_intercept</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>dataset</th>\n",
+              "      <th>drug</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>dose</th>\n",
+              "      <th>well_id</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
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+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"11\" valign=\"top\">13</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">(afatinib,)</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">BR1</th>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(1.86875e-11,)</th>\n",
+              "      <th>53868</th>\n",
+              "      <td>93</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.029535</td>\n",
+              "      <td>0.000915</td>\n",
+              "      <td>31.1</td>\n",
+              "      <td>6.269507</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>53869</th>\n",
+              "      <td>261</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.028068</td>\n",
+              "      <td>0.000787</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>5.714175</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(7.47625e-11,)</th>\n",
+              "      <th>53870</th>\n",
+              "      <td>92</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.028230</td>\n",
+              "      <td>0.000882</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>6.518346</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>53871</th>\n",
+              "      <td>260</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.029678</td>\n",
+              "      <td>0.000935</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>5.931319</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(3.0525e-10,)</th>\n",
+              "      <th>53872</th>\n",
+              "      <td>91</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.029814</td>\n",
+              "      <td>0.001067</td>\n",
+              "      <td>51.8</td>\n",
+              "      <td>6.501894</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">(trametinib,)</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">BR1</th>\n",
+              "      <th>(2.48e-08,)</th>\n",
+              "      <th>54143</th>\n",
+              "      <td>278</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.022501</td>\n",
+              "      <td>0.000752</td>\n",
+              "      <td>55.1</td>\n",
+              "      <td>6.505787</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(9.92125e-08,)</th>\n",
+              "      <th>54144</th>\n",
+              "      <td>109</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.011880</td>\n",
+              "      <td>0.001022</td>\n",
+              "      <td>55.1</td>\n",
+              "      <td>7.732698</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>54145</th>\n",
+              "      <td>277</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.016449</td>\n",
+              "      <td>0.001056</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>6.951063</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"2\" valign=\"top\">(3.96875e-07,)</th>\n",
+              "      <th>54146</th>\n",
+              "      <td>108</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.006953</td>\n",
+              "      <td>0.001200</td>\n",
+              "      <td>51.8</td>\n",
+              "      <td>7.678181</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>54147</th>\n",
+              "      <td>276</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>0.010494</td>\n",
+              "      <td>0.001388</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>6.785053</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>280 rows × 6 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8f52d40d-211a-41fc-af89-a909d36b8103')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-8f52d40d-211a-41fc-af89-a909d36b8103 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-8f52d40d-211a-41fc-af89-a909d36b8103');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-a4893a7b-90e2-41c0-b4de-e7869ba6bbc9\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a4893a7b-90e2-41c0-b4de-e7869ba6bbc9')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-a4893a7b-90e2-41c0-b4de-e7869ba6bbc9 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "summary": "{\n  \"name\": \"expt_diprates[expt_diprates\",\n  \"rows\": 280,\n  \"fields\": [\n    {\n      \"column\": \"well_num\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 97,\n        \"min\": 26,\n        \"max\": 357,\n        \"num_unique_values\": 280,\n        \"samples\": [\n          351,\n          79,\n          155\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"plate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"HTS001_BR1-2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.012155640277855975,\n        \"min\": -0.025586330800129703,\n        \"max\": 0.03664018208696803,\n        \"num_unique_values\": 280,\n        \"samples\": [\n          -0.012379989240099852\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_fit_std_err\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.000714178704949969,\n        \"min\": 0.00026565664853839174,\n        \"max\": 0.008725219858360715,\n        \"num_unique_values\": 280,\n        \"samples\": [\n          0.0009729437158239546\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_first_timepoint\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 18.403438559661954,\n        \"min\": 5.7,\n        \"max\": 108.3,\n        \"num_unique_values\": 14,\n        \"samples\": [\n          5.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_y_intercept\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5269932523295303,\n        \"min\": 2.385729022680922,\n        \"max\": 7.825645696563136,\n        \"num_unique_values\": 280,\n        \"samples\": [\n          6.064589351056325\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 14
+        }
+      ],
+      "source": [
+        "expt_diprates[expt_diprates.index.isin(['BR1'], level='cell_line')]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {
+        "id": "pPWd7RcSqi-U"
+      },
+      "outputs": [],
+      "source": [
+        "br1_afat = afat.filter(cell_lines=['BR1'])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "QT0ntlpeTACo"
+      },
+      "source": [
+        "### Plot the time course data of afatinib on BR1 cells\n",
+        "Use `log_yaxis=True` to plot population doublings."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 417
+        },
+        "id": "r8cpivoutCVg",
+        "outputId": "d4568a02-f626-4e70-96cd-bcc01845363a"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
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+              "<head><meta charset=\"utf-8\" /></head>\n",
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               {\"responsive\": true}                    ).then(function(){\n",
+              "                            \n",
+              "var gd = document.getElementById('3c73044f-6e28-4cd2-b67e-a75a2c71d1dd');\n",
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+              "            Plotly.purge(gd);\n",
+              "            observer.disconnect();\n",
+              "        }}\n",
+              "}});\n",
+              "\n",
+              "// Listen for the removal of the full notebook cells\n",
+              "var notebookContainer = gd.closest('#notebook-container');\n",
+              "if (notebookContainer) {{\n",
+              "    x.observe(notebookContainer, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "// Listen for the clearing of the current output cell\n",
+              "var outputEl = gd.closest('.output');\n",
+              "if (outputEl) {{\n",
+              "    x.observe(outputEl, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "                        })                };                            </script>        </div>\n",
+              "</body>\n",
+              "</html>"
+            ]
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "fig = plot_time_course(br1_afat, log_yaxis=True)\n",
+        "fig.update_layout(\n",
+        "    autosize=False,\n",
+        "    width=400,\n",
+        "    height=400,)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9qEn2v8uSPOH"
+      },
+      "source": [
+        "### Writing and reading cell count data using Vanderbilt's HTS format\n",
+        "To faciltate executing Python code, we will replace the `.` in column names with `_`."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 206
+        },
+        "id": "GOasPqwO6j5y",
+        "outputId": "ec01905c-e835-4582-fd97-0c6ec920d254"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "      drug1 cell_line    drug1_conc well          upid  time  cell_count  \\\n",
+              "0  afatinib       BR1  1.868750e-11  D22  HTS001_BR1-2   5.7        49.0   \n",
+              "1  afatinib       BR1  1.868750e-11  D22  HTS001_BR1-2   9.0        59.0   \n",
+              "2  afatinib       BR1  1.868750e-11  D22  HTS001_BR1-2  21.1        93.0   \n",
+              "3  afatinib       BR1  1.868750e-11  D22  HTS001_BR1-2  24.4       100.0   \n",
+              "4  afatinib       BR1  1.868750e-11  D22  HTS001_BR1-2  27.8       115.0   \n",
+              "\n",
+              "  drug1_units  \n",
+              "0           M  \n",
+              "1           M  \n",
+              "2           M  \n",
+              "3           M  \n",
+              "4           M  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-ea431f83-fcf7-446e-9978-f21e54665e09\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
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+              "\n",
+              "    .dataframe thead th {\n",
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+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>drug1</th>\n",
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+              "      <th>well</th>\n",
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+              "      <td>1.868750e-11</td>\n",
+              "      <td>D22</td>\n",
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+              "      <td>49.0</td>\n",
+              "      <td>M</td>\n",
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+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>afatinib</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>1.868750e-11</td>\n",
+              "      <td>D22</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>9.0</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>M</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>afatinib</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>1.868750e-11</td>\n",
+              "      <td>D22</td>\n",
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+              "      <td>93.0</td>\n",
+              "      <td>M</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>afatinib</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>1.868750e-11</td>\n",
+              "      <td>D22</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>24.4</td>\n",
+              "      <td>100.0</td>\n",
+              "      <td>M</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>afatinib</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>1.868750e-11</td>\n",
+              "      <td>D22</td>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>27.8</td>\n",
+              "      <td>115.0</td>\n",
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+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-323ca0a9-2395-4fcc-a112-520c5c054fef button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "a",
+              "summary": "{\n  \"name\": \"a\",\n  \"rows\": 7584,\n  \"fields\": [\n    {\n      \"column\": \"drug1\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"control\",\n          \"afatinib\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cell_line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"BR1\",\n          \"DS3\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"drug1_conc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8.071601162409352e-07,\n        \"min\": 0.0,\n        \"max\": 3.96875e-06,\n        \"num_unique_values\": 11,\n        \"samples\": [\n          1.55e-08,\n          1.86875e-11\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"well\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"L2\",\n          \"G2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"upid\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"HTS001_BR1-2\",\n          \"HTS001_DS3-2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"time\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 36.272506728557374,\n        \"min\": 0.5,\n        \"max\": 118.1,\n        \"num_unique_values\": 158,\n        \"samples\": [\n          58.8,\n          113.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cell_count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 407.1850762346451,\n        \"min\": 13.0,\n        \"max\": 2540.0,\n        \"num_unique_values\": 1351,\n        \"samples\": [\n          185.0,\n          355.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"drug1_units\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"M\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 17
+        }
+      ],
+      "source": [
+        "from pandas.io.parsers.readers import read_csv\n",
+        "if not os.path.exists(\"./data/afatinib.csv\"):\n",
+        "    thunor.io.write_vanderbilt_hts(afat, filename=\"./data/afatinib.csv\")\n",
+        "a = read_csv(\"./data/afatinib.csv\")\n",
+        "a.rename(columns={'cell.line': 'cell_line', 'cell.count': 'cell_count', 'drug1.conc': 'drug1_conc', 'drug1.units': 'drug1_units'}, inplace=True)\n",
+        "a.head()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "2cPtbROeRY57"
+      },
+      "source": [
+        "### Assemble basic DataFrame of DIP rates of control and paclitaxel-treated BR1 cells\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "hff1tpp6Mcw6",
+        "outputId": "2d278ce4-e8ad-44c4-c7d2-33c03ca113cd"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "<ipython-input-18-298717f31f1e>:5: FutureWarning:\n",
+            "\n",
+            "The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "diprates_br1_pacl = hts001_diprates[np.isin(hts001_diprates['drug'], ['paclitaxel']) ]\n",
+        "diprates_br1_pacl = diprates_br1_pacl[diprates_br1_pacl['cell_line'] == 'BR1']\n",
+        "# add control diprates\n",
+        "br1_diprates_ctrl = hts001_diprates[np.logical_and(hts001_diprates['conc'].isna(), hts001_diprates['cell_line']=='BR1')]\n",
+        "diprates_br1_pacl = diprates_br1_pacl.append(br1_diprates_ctrl)\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HPnIPXBsTalD"
+      },
+      "source": [
+        "### Add log10([drug]) values to facilitate manual plotting"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 206
+        },
+        "id": "KJNJPynIVlsz",
+        "outputId": "9f8cfecc-0dc6-4cda-bfc0-340a9ffaa7c0"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "            plate well cell_line        drug          conc  dip_rate  \\\n",
+              "121  HTS001_BR1-2  G13       BR1  paclitaxel  3.968750e-06 -0.006813   \n",
+              "122  HTS001_BR1-2  G14       BR1  paclitaxel  9.921250e-07 -0.005648   \n",
+              "123  HTS001_BR1-2  G15       BR1  paclitaxel  2.480000e-07 -0.025586   \n",
+              "124  HTS001_BR1-2  G16       BR1  paclitaxel  6.201250e-08  0.029093   \n",
+              "125  HTS001_BR1-2  G17       BR1  paclitaxel  1.550000e-08 -0.007844   \n",
+              "\n",
+              "     dip_fit_std_err  l10_conc  \n",
+              "121         0.000790 -5.401346  \n",
+              "122         0.001530 -6.003434  \n",
+              "123         0.002220 -6.605548  \n",
+              "124         0.000726 -7.207521  \n",
+              "125         0.001042 -7.809668  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-b62a56dc-d7ce-4d7d-9e57-cc6d6131ef4b\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>plate</th>\n",
+              "      <th>well</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>drug</th>\n",
+              "      <th>conc</th>\n",
+              "      <th>dip_rate</th>\n",
+              "      <th>dip_fit_std_err</th>\n",
+              "      <th>l10_conc</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>121</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G13</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.968750e-06</td>\n",
+              "      <td>-0.006813</td>\n",
+              "      <td>0.000790</td>\n",
+              "      <td>-5.401346</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>122</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G14</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>9.921250e-07</td>\n",
+              "      <td>-0.005648</td>\n",
+              "      <td>0.001530</td>\n",
+              "      <td>-6.003434</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>123</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G15</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>2.480000e-07</td>\n",
+              "      <td>-0.025586</td>\n",
+              "      <td>0.002220</td>\n",
+              "      <td>-6.605548</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>124</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G16</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>6.201250e-08</td>\n",
+              "      <td>0.029093</td>\n",
+              "      <td>0.000726</td>\n",
+              "      <td>-7.207521</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>125</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G17</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.550000e-08</td>\n",
+              "      <td>-0.007844</td>\n",
+              "      <td>0.001042</td>\n",
+              "      <td>-7.809668</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b62a56dc-d7ce-4d7d-9e57-cc6d6131ef4b')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-b62a56dc-d7ce-4d7d-9e57-cc6d6131ef4b button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-b62a56dc-d7ce-4d7d-9e57-cc6d6131ef4b');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-4c8c6383-6479-43ac-b709-4d3cac71b88a\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4c8c6383-6479-43ac-b709-4d3cac71b88a')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-4c8c6383-6479-43ac-b709-4d3cac71b88a button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "diprates_br1_pacl",
+              "summary": "{\n  \"name\": \"diprates_br1_pacl\",\n  \"rows\": 48,\n  \"fields\": [\n    {\n      \"column\": \"plate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"HTS001_BR1-2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"well\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"E23\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cell_line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"BR1\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"drug\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"paclitaxel\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"conc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.213981259444919e-06,\n        \"min\": 1.86875e-11,\n        \"max\": 3.96875e-06,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          7.47625e-11\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.017577502405059058,\n        \"min\": -0.0255863308001297,\n        \"max\": 0.036349421359956,\n        \"num_unique_values\": 48,\n        \"samples\": [\n          0.0355824141677683\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_fit_std_err\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.00028605136994977036,\n        \"min\": 0.0005026613546363,\n        \"max\": 0.0022195623350899,\n        \"num_unique_values\": 48,\n        \"samples\": [\n          0.0010395076275443\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"l10_conc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.128820024585955,\n        \"min\": -11.728448794331495,\n        \"max\": -5.401346257363949,\n        \"num_unique_values\": 11,\n        \"samples\": [\n          -8.429457060118102\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 19
+        }
+      ],
+      "source": [
+        "l10_conc = np.log10(diprates_br1_pacl['conc'][diprates_br1_pacl['conc'].notna()])\n",
+        "min_conc = min(l10_conc)-1\n",
+        "n_ctrl_wells = len( diprates_br1_pacl['conc'][diprates_br1_pacl['conc'].isna()])\n",
+        "l10_conc = np.append(l10_conc,np.repeat(min_conc,n_ctrl_wells))\n",
+        "diprates_br1_pacl['l10_conc'] = l10_conc\n",
+        "diprates_br1_pacl.head()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "1dnCbIvOTutf"
+      },
+      "source": [
+        "### Calculate response ratio of DIP rates\n",
+        "Divide all DIP rate values by the mean of the control values"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "id": "iLGN0Ki3cnUA"
+      },
+      "outputs": [],
+      "source": [
+        "diprates_br1_pacl[\"resp_ratio\"] = diprates_br1_pacl[\"dip_rate\"] / diprates_br1_pacl[diprates_br1_pacl[\"conc\"].isnull()][\"dip_rate\"].mean()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Xh3_KSQ3e9ru"
+      },
+      "source": [
+        "### Show the structure of the DataFrame"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 21,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "AZTZEtvPdAqI",
+        "outputId": "e2b46a32-35b5-4caf-bcd8-9ab652c307a0"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "            plate well cell_line        drug          conc  dip_rate  \\\n",
+              "121  HTS001_BR1-2  G13       BR1  paclitaxel  3.968750e-06 -0.006813   \n",
+              "122  HTS001_BR1-2  G14       BR1  paclitaxel  9.921250e-07 -0.005648   \n",
+              "123  HTS001_BR1-2  G15       BR1  paclitaxel  2.480000e-07 -0.025586   \n",
+              "124  HTS001_BR1-2  G16       BR1  paclitaxel  6.201250e-08  0.029093   \n",
+              "125  HTS001_BR1-2  G17       BR1  paclitaxel  1.550000e-08 -0.007844   \n",
+              "126  HTS001_BR1-2  G18       BR1  paclitaxel  3.720000e-09 -0.005186   \n",
+              "127  HTS001_BR1-2  G19       BR1  paclitaxel  1.246000e-09  0.015638   \n",
+              "128  HTS001_BR1-2  G20       BR1  paclitaxel  3.052500e-10  0.004428   \n",
+              "129  HTS001_BR1-2  G21       BR1  paclitaxel  7.476250e-11  0.026220   \n",
+              "130  HTS001_BR1-2  G22       BR1  paclitaxel  1.868750e-11  0.027360   \n",
+              "275  HTS001_BR1-2  N13       BR1  paclitaxel  3.968750e-06 -0.012822   \n",
+              "276  HTS001_BR1-2  N14       BR1  paclitaxel  9.921250e-07 -0.007132   \n",
+              "277  HTS001_BR1-2  N15       BR1  paclitaxel  2.480000e-07 -0.005049   \n",
+              "278  HTS001_BR1-2  N16       BR1  paclitaxel  6.201250e-08  0.025072   \n",
+              "279  HTS001_BR1-2  N17       BR1  paclitaxel  1.550000e-08 -0.009993   \n",
+              "280  HTS001_BR1-2  N18       BR1  paclitaxel  3.720000e-09 -0.002775   \n",
+              "281  HTS001_BR1-2  N19       BR1  paclitaxel  1.246000e-09  0.015146   \n",
+              "282  HTS001_BR1-2  N20       BR1  paclitaxel  3.052500e-10 -0.004723   \n",
+              "283  HTS001_BR1-2  N21       BR1  paclitaxel  7.476250e-11  0.028929   \n",
+              "284  HTS001_BR1-2  N22       BR1  paclitaxel  1.868750e-11  0.027242   \n",
+              "0    HTS001_BR1-2   B2       BR1         NaN           NaN  0.033001   \n",
+              "21   HTS001_BR1-2  B23       BR1         NaN           NaN  0.030042   \n",
+              "22   HTS001_BR1-2   C2       BR1         NaN           NaN  0.032687   \n",
+              "43   HTS001_BR1-2  C23       BR1         NaN           NaN  0.033225   \n",
+              "44   HTS001_BR1-2   D2       BR1         NaN           NaN  0.035573   \n",
+              "65   HTS001_BR1-2  D23       BR1         NaN           NaN  0.031708   \n",
+              "66   HTS001_BR1-2   E2       BR1         NaN           NaN  0.027436   \n",
+              "87   HTS001_BR1-2  E23       BR1         NaN           NaN  0.035582   \n",
+              "88   HTS001_BR1-2   F2       BR1         NaN           NaN  0.034431   \n",
+              "109  HTS001_BR1-2  F23       BR1         NaN           NaN  0.036349   \n",
+              "110  HTS001_BR1-2   G2       BR1         NaN           NaN  0.032397   \n",
+              "131  HTS001_BR1-2  G23       BR1         NaN           NaN  0.032519   \n",
+              "132  HTS001_BR1-2   H2       BR1         NaN           NaN  0.034271   \n",
+              "153  HTS001_BR1-2  H23       BR1         NaN           NaN  0.033809   \n",
+              "154  HTS001_BR1-2   I2       BR1         NaN           NaN  0.027382   \n",
+              "175  HTS001_BR1-2  I23       BR1         NaN           NaN  0.035187   \n",
+              "176  HTS001_BR1-2   J2       BR1         NaN           NaN  0.031205   \n",
+              "197  HTS001_BR1-2  J23       BR1         NaN           NaN  0.035118   \n",
+              "198  HTS001_BR1-2   K2       BR1         NaN           NaN  0.030545   \n",
+              "219  HTS001_BR1-2  K23       BR1         NaN           NaN  0.034301   \n",
+              "220  HTS001_BR1-2   L2       BR1         NaN           NaN  0.035195   \n",
+              "241  HTS001_BR1-2  L23       BR1         NaN           NaN  0.031155   \n",
+              "242  HTS001_BR1-2   M2       BR1         NaN           NaN  0.034813   \n",
+              "263  HTS001_BR1-2  M23       BR1         NaN           NaN  0.030340   \n",
+              "264  HTS001_BR1-2   N2       BR1         NaN           NaN  0.031966   \n",
+              "285  HTS001_BR1-2  N23       BR1         NaN           NaN  0.034938   \n",
+              "286  HTS001_BR1-2   O2       BR1         NaN           NaN  0.028940   \n",
+              "307  HTS001_BR1-2  O23       BR1         NaN           NaN  0.029751   \n",
+              "\n",
+              "     dip_fit_std_err   l10_conc  resp_ratio  \n",
+              "121         0.000790  -5.401346   -0.208729  \n",
+              "122         0.001530  -6.003434   -0.173044  \n",
+              "123         0.002220  -6.605548   -0.783940  \n",
+              "124         0.000726  -7.207521    0.891395  \n",
+              "125         0.001042  -7.809668   -0.240335  \n",
+              "126         0.000742  -8.429457   -0.158888  \n",
+              "127         0.000616  -8.904482    0.479145  \n",
+              "128         0.001103  -9.515344    0.135681  \n",
+              "129         0.000946 -10.126316    0.803353  \n",
+              "130         0.000709 -10.728449    0.838293  \n",
+              "275         0.001204  -5.401346   -0.392861  \n",
+              "276         0.000678  -6.003434   -0.218516  \n",
+              "277         0.001077  -6.605548   -0.154684  \n",
+              "278         0.000853  -7.207521    0.768178  \n",
+              "279         0.000750  -7.809668   -0.306173  \n",
+              "280         0.000718  -8.429457   -0.085035  \n",
+              "281         0.000503  -8.904482    0.464053  \n",
+              "282         0.000753  -9.515344   -0.144700  \n",
+              "283         0.001043 -10.126316    0.886361  \n",
+              "284         0.000910 -10.728449    0.834670  \n",
+              "0           0.001192 -11.728449    1.011128  \n",
+              "21          0.001095 -11.728449    0.920465  \n",
+              "22          0.000875 -11.728449    1.001501  \n",
+              "43          0.000673 -11.728449    1.017994  \n",
+              "44          0.001224 -11.728449    1.089917  \n",
+              "65          0.001096 -11.728449    0.971499  \n",
+              "66          0.000689 -11.728449    0.840612  \n",
+              "87          0.001040 -11.728449    1.090210  \n",
+              "88          0.001310 -11.728449    1.054923  \n",
+              "109         0.001164 -11.728449    1.113710  \n",
+              "110         0.000938 -11.728449    0.992599  \n",
+              "131         0.001027 -11.728449    0.996342  \n",
+              "132         0.001215 -11.728449    1.050026  \n",
+              "153         0.000782 -11.728449    1.035880  \n",
+              "154         0.000795 -11.728449    0.838952  \n",
+              "175         0.001015 -11.728449    1.078092  \n",
+              "176         0.001214 -11.728449    0.956079  \n",
+              "197         0.001112 -11.728449    1.075994  \n",
+              "198         0.000884 -11.728449    0.935853  \n",
+              "219         0.000901 -11.728449    1.050963  \n",
+              "220         0.001343 -11.728449    1.078353  \n",
+              "241         0.001227 -11.728449    0.954570  \n",
+              "242         0.001014 -11.728449    1.066627  \n",
+              "263         0.001009 -11.728449    0.929589  \n",
+              "264         0.001306 -11.728449    0.979409  \n",
+              "285         0.001046 -11.728449    1.070477  \n",
+              "286         0.000770 -11.728449    0.886694  \n",
+              "307         0.001153 -11.728449    0.911542  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-a99176ec-d999-4cdc-a4e7-4762f498ffdd\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>plate</th>\n",
+              "      <th>well</th>\n",
+              "      <th>cell_line</th>\n",
+              "      <th>drug</th>\n",
+              "      <th>conc</th>\n",
+              "      <th>dip_rate</th>\n",
+              "      <th>dip_fit_std_err</th>\n",
+              "      <th>l10_conc</th>\n",
+              "      <th>resp_ratio</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>121</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G13</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.968750e-06</td>\n",
+              "      <td>-0.006813</td>\n",
+              "      <td>0.000790</td>\n",
+              "      <td>-5.401346</td>\n",
+              "      <td>-0.208729</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>122</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G14</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>9.921250e-07</td>\n",
+              "      <td>-0.005648</td>\n",
+              "      <td>0.001530</td>\n",
+              "      <td>-6.003434</td>\n",
+              "      <td>-0.173044</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>123</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G15</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>2.480000e-07</td>\n",
+              "      <td>-0.025586</td>\n",
+              "      <td>0.002220</td>\n",
+              "      <td>-6.605548</td>\n",
+              "      <td>-0.783940</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>124</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G16</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>6.201250e-08</td>\n",
+              "      <td>0.029093</td>\n",
+              "      <td>0.000726</td>\n",
+              "      <td>-7.207521</td>\n",
+              "      <td>0.891395</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>125</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G17</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.550000e-08</td>\n",
+              "      <td>-0.007844</td>\n",
+              "      <td>0.001042</td>\n",
+              "      <td>-7.809668</td>\n",
+              "      <td>-0.240335</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>126</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G18</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.720000e-09</td>\n",
+              "      <td>-0.005186</td>\n",
+              "      <td>0.000742</td>\n",
+              "      <td>-8.429457</td>\n",
+              "      <td>-0.158888</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>127</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G19</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.246000e-09</td>\n",
+              "      <td>0.015638</td>\n",
+              "      <td>0.000616</td>\n",
+              "      <td>-8.904482</td>\n",
+              "      <td>0.479145</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G20</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.052500e-10</td>\n",
+              "      <td>0.004428</td>\n",
+              "      <td>0.001103</td>\n",
+              "      <td>-9.515344</td>\n",
+              "      <td>0.135681</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>129</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G21</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>7.476250e-11</td>\n",
+              "      <td>0.026220</td>\n",
+              "      <td>0.000946</td>\n",
+              "      <td>-10.126316</td>\n",
+              "      <td>0.803353</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>130</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G22</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.868750e-11</td>\n",
+              "      <td>0.027360</td>\n",
+              "      <td>0.000709</td>\n",
+              "      <td>-10.728449</td>\n",
+              "      <td>0.838293</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>275</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N13</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.968750e-06</td>\n",
+              "      <td>-0.012822</td>\n",
+              "      <td>0.001204</td>\n",
+              "      <td>-5.401346</td>\n",
+              "      <td>-0.392861</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>276</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N14</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>9.921250e-07</td>\n",
+              "      <td>-0.007132</td>\n",
+              "      <td>0.000678</td>\n",
+              "      <td>-6.003434</td>\n",
+              "      <td>-0.218516</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>277</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N15</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>2.480000e-07</td>\n",
+              "      <td>-0.005049</td>\n",
+              "      <td>0.001077</td>\n",
+              "      <td>-6.605548</td>\n",
+              "      <td>-0.154684</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>278</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N16</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>6.201250e-08</td>\n",
+              "      <td>0.025072</td>\n",
+              "      <td>0.000853</td>\n",
+              "      <td>-7.207521</td>\n",
+              "      <td>0.768178</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>279</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N17</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.550000e-08</td>\n",
+              "      <td>-0.009993</td>\n",
+              "      <td>0.000750</td>\n",
+              "      <td>-7.809668</td>\n",
+              "      <td>-0.306173</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>280</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N18</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.720000e-09</td>\n",
+              "      <td>-0.002775</td>\n",
+              "      <td>0.000718</td>\n",
+              "      <td>-8.429457</td>\n",
+              "      <td>-0.085035</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>281</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N19</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.246000e-09</td>\n",
+              "      <td>0.015146</td>\n",
+              "      <td>0.000503</td>\n",
+              "      <td>-8.904482</td>\n",
+              "      <td>0.464053</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>282</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N20</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>3.052500e-10</td>\n",
+              "      <td>-0.004723</td>\n",
+              "      <td>0.000753</td>\n",
+              "      <td>-9.515344</td>\n",
+              "      <td>-0.144700</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>283</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N21</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>7.476250e-11</td>\n",
+              "      <td>0.028929</td>\n",
+              "      <td>0.001043</td>\n",
+              "      <td>-10.126316</td>\n",
+              "      <td>0.886361</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>284</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N22</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>paclitaxel</td>\n",
+              "      <td>1.868750e-11</td>\n",
+              "      <td>0.027242</td>\n",
+              "      <td>0.000910</td>\n",
+              "      <td>-10.728449</td>\n",
+              "      <td>0.834670</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.033001</td>\n",
+              "      <td>0.001192</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.011128</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>B23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.030042</td>\n",
+              "      <td>0.001095</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.920465</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>C2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.032687</td>\n",
+              "      <td>0.000875</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.001501</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>43</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>C23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.033225</td>\n",
+              "      <td>0.000673</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.017994</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>44</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>D2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.035573</td>\n",
+              "      <td>0.001224</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.089917</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>65</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>D23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.031708</td>\n",
+              "      <td>0.001096</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.971499</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>66</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>E2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.027436</td>\n",
+              "      <td>0.000689</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.840612</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>87</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>E23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.035582</td>\n",
+              "      <td>0.001040</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.090210</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>88</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>F2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.034431</td>\n",
+              "      <td>0.001310</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.054923</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>109</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>F23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.036349</td>\n",
+              "      <td>0.001164</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.113710</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>110</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.032397</td>\n",
+              "      <td>0.000938</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.992599</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>131</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>G23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.032519</td>\n",
+              "      <td>0.001027</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.996342</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>132</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>H2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.034271</td>\n",
+              "      <td>0.001215</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.050026</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>153</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>H23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.033809</td>\n",
+              "      <td>0.000782</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.035880</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>154</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>I2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.027382</td>\n",
+              "      <td>0.000795</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.838952</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>175</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>I23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.035187</td>\n",
+              "      <td>0.001015</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.078092</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>176</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>J2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.031205</td>\n",
+              "      <td>0.001214</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.956079</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>197</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>J23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.035118</td>\n",
+              "      <td>0.001112</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.075994</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>198</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>K2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.030545</td>\n",
+              "      <td>0.000884</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.935853</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>219</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>K23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.034301</td>\n",
+              "      <td>0.000901</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.050963</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>220</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>L2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.035195</td>\n",
+              "      <td>0.001343</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.078353</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>241</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>L23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.031155</td>\n",
+              "      <td>0.001227</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.954570</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>242</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>M2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.034813</td>\n",
+              "      <td>0.001014</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.066627</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>263</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>M23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.030340</td>\n",
+              "      <td>0.001009</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.929589</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>264</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.031966</td>\n",
+              "      <td>0.001306</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.979409</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>285</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>N23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.034938</td>\n",
+              "      <td>0.001046</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>1.070477</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>286</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>O2</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.028940</td>\n",
+              "      <td>0.000770</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.886694</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>307</th>\n",
+              "      <td>HTS001_BR1-2</td>\n",
+              "      <td>O23</td>\n",
+              "      <td>BR1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0.029751</td>\n",
+              "      <td>0.001153</td>\n",
+              "      <td>-11.728449</td>\n",
+              "      <td>0.911542</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a99176ec-d999-4cdc-a4e7-4762f498ffdd')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-a99176ec-d999-4cdc-a4e7-4762f498ffdd button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-a99176ec-d999-4cdc-a4e7-4762f498ffdd');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-ba9af673-38ee-4032-9566-09aa267882d3\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ba9af673-38ee-4032-9566-09aa267882d3')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-ba9af673-38ee-4032-9566-09aa267882d3 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "diprates_br1_pacl",
+              "summary": "{\n  \"name\": \"diprates_br1_pacl\",\n  \"rows\": 48,\n  \"fields\": [\n    {\n      \"column\": \"plate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"HTS001_BR1-2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"well\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"E23\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cell_line\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"BR1\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"drug\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"paclitaxel\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"conc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.213981259444919e-06,\n        \"min\": 1.86875e-11,\n        \"max\": 3.96875e-06,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          7.47625e-11\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.017577502405059058,\n        \"min\": -0.0255863308001297,\n        \"max\": 0.036349421359956,\n        \"num_unique_values\": 48,\n        \"samples\": [\n          0.0355824141677683\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dip_fit_std_err\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.00028605136994977036,\n        \"min\": 0.0005026613546363,\n        \"max\": 0.0022195623350899,\n        \"num_unique_values\": 48,\n        \"samples\": [\n          0.0010395076275443\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"l10_conc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.128820024585955,\n        \"min\": -11.728448794331495,\n        \"max\": -5.401346257363949,\n        \"num_unique_values\": 11,\n        \"samples\": [\n          -8.429457060118102\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"resp_ratio\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5385570874129337,\n        \"min\": -0.7839395766110487,\n        \"max\": 1.113709902900031,\n        \"num_unique_values\": 48,\n        \"samples\": [\n          1.0902095699215248\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 21
+        }
+      ],
+      "source": [
+        "diprates_br1_pacl"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "l3rROG4NfFdZ"
+      },
+      "source": [
+        "### Plot the DIP rate values of BR1 cells treated with paclitaxel using Seaborn"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 524
+        },
+        "id": "3qyXL0sFUPK5",
+        "outputId": "b642c271-758c-4f8c-e1df-037787d168df"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<seaborn.axisgrid.FacetGrid at 0x7f07820ad810>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 22
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x500 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "sns.lmplot(x='l10_conc', y='dip_rate', data=diprates_br1_pacl, fit_reg=False)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "w1RHibjn6j5y"
+      },
+      "source": [
+        "#### Perform nonlinear regression on data using the `ll4` model  \n",
+        "Let's first look at each of the dates independently to assess consistency.  \n",
+        "#### Use `scipy.optimize.curve_fit` to perform nonlinear regression (fit model parameters)  \n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        " fitCoefs, covMatrix = opt.curve_fit(ll4,\n",
+        "                                    10**(diprates_br1_pacl['l10_conc']),\n",
+        "                                    diprates_br1_pacl['dip_rate'],\n",
+        "                                    p0=[1,\n",
+        "                                        np.max(diprates_br1_pacl['dip_rate']),\n",
+        "                                        np.min(diprates_br1_pacl['dip_rate']),\n",
+        "                                        1e-9])\n",
+        " fitCoefs"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KY_f5068B6Zi",
+        "outputId": "2f5dee8f-ae58-441b-ac7b-0a8b82433abe"
+      },
+      "execution_count": 29,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "array([ 2.69527518e-01,  4.99380965e-02, -9.96981366e-03,  5.57458520e-11])"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 29
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "weYYiyir98XD"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ud9_lflbZLDr"
+      },
+      "source": [
+        "# TASK\n",
+        "\n",
+        "What is the value that represents the $EC_{50}$ of paclitaxel's effects on BR1 cells? Copy it and save as the answer to Quiz question #6."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "6djHmEe2UZ40"
+      },
+      "source": [
+        "### NOTE: Values from paclitaxel of ~6.2e-8 M were found to be artifactual\n",
+        "Drug concentration at this value is inaccurate. Data can be removed to allow more accurate fitting of dose-response model"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "metadata": {
+        "id": "HzmXGZlUJgG5"
+      },
+      "outputs": [],
+      "source": [
+        "# remove artifact points\n",
+        "diprates_br1_pacl_drop62 = diprates_br1_pacl[np.logical_or(diprates_br1_pacl['conc'] < 2e-8, diprates_br1_pacl['conc'] > 7e-8)]\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "hv7q1rLRV52C"
+      },
+      "source": [
+        "# TASK\n",
+        "### Fit the cleaned data with the `ll4` model\n",
+        "NOTE: to get the model to fit you may need some starting parameters (`p0`)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "5vTCa3O_ilGJ"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 32,
+      "metadata": {
+        "id": "z-foKIdsaO_X",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "6625bbcb-a5e6-4b14-f46d-b342ac87640e"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "array([ 5.24235174e-01,  3.96443004e-02, -1.12955545e-02,  2.23335887e-10])"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 32
+        }
+      ],
+      "source": [
+        "fitCoefs_dropped, covMatrix_dropped = opt.curve_fit(ll4,\n",
+        "                                    10**(diprates_br1_pacl_drop62['l10_conc']),\n",
+        "                                    diprates_br1_pacl_drop62['dip_rate'],\n",
+        "                                    p0=[1,\n",
+        "                                        np.max(diprates_br1_pacl_drop62['dip_rate']),\n",
+        "                                        np.min(diprates_br1_pacl_drop62['dip_rate']),\n",
+        "                                        1e-9])\n",
+        "\n",
+        "fitCoefs_dropped  # show the values of the fit parameters; leave this line in"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "M-yAXIuzWWZJ"
+      },
+      "source": [
+        "# TASK\n",
+        "\n",
+        "Copy the value that represents the corrected $EC_{50}$ of paclitaxel's effects on BR1 cells and save as the answer to Quiz question #7."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "jxhb_Ly96j5y"
+      },
+      "source": [
+        "#### Plot the data and predicted model fits using Seaborn\n",
+        "NOTE: You will see two curves if you properly fit the cleaned data with the `ll4` model and saved the fit parameters in `fitCoefs_dropped`  "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 33,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 525
+        },
+        "id": "UK4klnJbZlpx",
+        "outputId": "e1301aee-e534-4329-d4bb-d7b7dc5b9209"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<Axes: xlabel='l10_conc', ylabel='dip_rate'>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 33
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x500 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "myconc = np.linspace(-12,-5,100)\n",
+        "sns.lmplot(x='l10_conc', y='dip_rate', data=diprates_br1_pacl, fit_reg=False)\n",
+        "if type(fitCoefs_dropped)!=int:\n",
+        "    sns.lineplot(x=myconc, y=[ll4(x, *fitCoefs_dropped) for x in 10**myconc], legend=False)\n",
+        "sns.lineplot(x=myconc, y=[ll4(x, *fitCoefs) for x in 10**myconc], legend=False, hue=2)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "MfIG6Kno6j5z"
+      },
+      "source": [
+        "#### Perform nonlinear regression on data using `ll3` model  \n",
+        "Use `resp_ratio` values.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 34,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "3Ue2Rwp56j5z",
+        "outputId": "818b33d5-7093-4f4e-ab4e-97e0049bf16d"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "array([ 6.15594008e-01, -3.36526687e-01,  4.17293781e-10])"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 34
+        }
+      ],
+      "source": [
+        "fitCoefs_ratio, covMatrix_ratio = opt.curve_fit(ll3, 10**(diprates_br1_pacl_drop62['l10_conc']),\n",
+        "                                    diprates_br1_pacl_drop62['resp_ratio'])\n",
+        "fitCoefs_ratio"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "kBVmg7djf8xr"
+      },
+      "source": [
+        "# Task\n",
+        "What is the $E_{max}$ value from the `ll3` model parameters fit to response ratios of BR1 + paclitaxel? Copy it and save the answer to Quiz question #8."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "rDTanbu5uQ-9"
+      },
+      "source": [
+        "#### Plot the data and predicted model fits using Seaborn"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 35,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 512
+        },
+        "id": "v5Xn-Q566j5z",
+        "outputId": "86ede5ce-192e-4dd5-b6c1-4404677b1b1d"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 500x500 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "a = sns.lmplot(x='l10_conc', y='resp_ratio', data=diprates_br1_pacl_drop62, fit_reg=False)\n",
+        "a.set(ylim=(-1, 1.25))\n",
+        "l = sns.lineplot(x=[i for i in myconc], y=[ll3(10**i,*fitCoefs_ratio) for i in myconc], legend=False)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 36,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "LGkZX0_HbKw8",
+        "outputId": "3d9ad086-47b3-4e2e-d613-f8e7de2539c9"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "The EC50 of paclitaxel on BR1 cells is 0.417 nM\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(f\"The EC50 of paclitaxel on BR1 cells is {np.round(fitCoefs_ratio[2]*1e9,3)} nM\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "PFE-dblWbkWk"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.4"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file