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ashoks773/README.md

Hello, My name is Ashok Kumar Sharma and I am a Senior Bioinformatics Scientist at Cedars-Sinai Medical Center, specializing in analyzing a wide range of multi-modal datasets to uncover host-microbiome interactions and their role in animal and human health. My work focuses on developing and optimizing computational pipelines, leveraging AI/ML for biomarker discovery, and supporting translational research in digestive and liver diseases.


Research Interests

I am passionate about understanding complex biological systems through innovative computational approaches. My research focuses on developing and applying advanced bioinformatics tools, pipelines, and AI/ML models to analyze and integrate multi-omics datasets (genomics, transcriptomics, metabolomics, and proteomics) to uncover the molecular mechanisms underlying health and disease. Specifically, I am interested in:

  • Host-Microbiome Interactions: Investigating how microbial communities influence host physiology and contribute to diseases such as inflammatory bowel disease (IBD) and metabolic disorders.
  • Multi-Omics Data Integration: Designing scalable, reproducible pipelines to integrate and analyze diverse omics datasets, enabling biomarker discovery and systems-level insights.
  • AI/ML in Biology: Leveraging machine learning and statistical models for predictive analytics, patient stratification, and biomarker identification in translational and clinical research.
  • Spatial and Single-Cell Omics: Exploring cell-specific gene expression patterns and spatial organization of tissues to understand disease progression and therapeutic responses.
  • Translational Bioinformatics: Bridging computational biology and clinical research to develop data-driven solutions for personalized medicine and drug discovery.

My work is driven by a commitment to advancing biological knowledge through computational innovation, collaboration, and open science.


Professional Experience

  • Bioinformatics Scientist II, Cedars-Sinai (2024–Present)
    Providing computational support for multi-omics data analysis and integration, optimizing pipelines, and guiding experimental design to advance clinical and translational research in digestive and liver diseases

  • Scientist II, Computational Biology, Takeda Pharmaceuticals (2023–2024)
    Delivered AI/ML-driven safety risk assessments, predictive modeling, and transcriptomic analyses for drug discovery.

  • Postdoctoral Scientist, Cedars-Sinai (2021–2023)
    Investigated pathogenic factors in IBD using multi-omics approaches.

  • Postdoctoral Associate, University of Minnesota (2018–2021)
    Advanced microbiome-host interaction studies using multi-omics data analysis and integration.


Education

  • Ph.D. in Computational Biology (2013–2018) – IISER Bhopal
    Thesis: Development of Computational Models for the analysis of large-scale genomic and metagenomic datasets
  • M.S. in Pharmacoinformatics (2010–2012) – NIPER Mohali
    Thesis: Modeling and designing Glycogen Synthase Kinase-3 Inhibitors
  • B.Pharm (2006–2010) – Dr. H.S. Gour University

Publications & Projects

Explore my work on:


Collaborate or Connect

I am always open to discussing research ideas, data analysis challenges, or potential collaborations. If you would like to brainstorm or co-develop something impactful, don’t hesitate to get in touch! 📧 Email: compbiosharma@gmail.com or ashoks773@gmail.com

Popular repositories Loading

  1. Primates-Gut-Metagenome Primates-Gut-Metagenome Public

    Functional Adaptations in the Gut Microbiome to Analogous Ecological Conditions

    R 1

  2. Oral-microbiome-16S Oral-microbiome-16S Public

    Jupyter Notebook 1

  3. DILI_Bayesian_Model DILI_Bayesian_Model Public

    This repository contains example machine learning (ML) code for Bayesian Neural Networks (BNN) and fundamental modules adaptable for various projects.

    Jupyter Notebook 1

  4. mycobiome_bacteriome mycobiome_bacteriome Public

    The gut mycobiome-bacteriome interface is significantly impacted by subsistence strategy in humans and nonhuman primates

    R

  5. Bacterial_growth_rates Bacterial_growth_rates Public

    Computational pipeline to calculate bacterial growth rates from metagenomic samples

    Shell

  6. ashoks773.github.io ashoks773.github.io Public

    Forked from jonbarron/jonbarron.github.io

    Personal website

    HTML