Merge branch 'main' of https://github.com/bowang-lab/AGILE into main

Author: rexxxx1234

README.md

@@ -19,13 +19,36 @@ An overview of AGILE can be seen below:
 </p>
 
 
-## Future Release Plan
+## Getting Started
 
-- [x] Initial release
-- [x] Release data
-- [x] Release model code
-- [x] Release model pretraining, fine-tuning scripts
+### Installation
 
+Set up conda environment and clone the github repo
+
+```
+# create a new environment
+$ conda create --name agile python=3.9 -y
+$ conda activate agile
+
+# install requirements
+$ pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113  --extra-index-url https://download.pytorch.org/whl/cu113
+$ pip install torch-geometric==2.2.0 torch-sparse==0.6.16 torch-scatter==2.1.0 -f https://data.pyg.org/whl/torch-1.12.0+cu113.html
+$ pip install -r requirements.txt
+```
+### Pre-training
+
+The continuous pretraining of AGILE is inherited from [MolCLR](https://www.nature.com/articles/s42256-022-00447-x), the pre-trained MolCLR models can be found in [link](https://github.com/yuyangw/MolCLR). To pre-train with your own data, you can modify the configurations in `config_pretrain.yaml`. 
+```
+$ python pretrain.py config_pretrain.yaml
+```
+
+### Fine-tuning
+
+To fine-tune the AGILE pre-trained model for ionizable lipid prediction on the specific cell lines, you can modify the configurations in `config_finetune.yaml`. We have provided the pre-trained AGILE model on the 60k virtual lipid library, which can be found in `ckpt/pretrained_agile_60k`.
+
+```
+$ python finetune.py config_finetune.yaml
+```
 
 ## Citing AGILE
 
@@ -39,3 +62,7 @@ An overview of AGILE can be seen below:
   publisher={Cold Spring Harbor Laboratory}
 }
 ```
+## Acknowledgement
+
+- MolCLR: [https://github.com/yuyangw/MolCLR](https://github.com/yuyangw/MolCLR)
+- Mordred: [https://github.com/mordred-descriptor/mordred](https://github.com/mordred-descriptor/mordred)