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Stochastic Modeling of the Immune System, A Multiscale Challenge.

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We develop new bioinformatics pipeline for systems biology at all scales.
Then, we make stochastic models combining all these scales together.

  • 🔭 Our current research interests in Healthcare cover:
    • [repo] Drug Target discovery
    • [repo] Gene regulatory networks
    • [repo] Antigen-Antibody binding
    • [repo] Antibody repertoire analysis
    • [repo] Non-Markovian stochastic systems
    • [repo] Multi-scale hybrid models of the immune system
    • [repo] Raman Microscopy for Disease diagnosis
    • Single-cell RNA-seq analysis
    • Quantum Machine Learning for Healthcare applications

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  1. Germinal-Center Germinal-Center Public

    A Probabilistic agent based model of the Germinal Center reaction, with explicit modeling of mutations in the B cell receptors sequences.

    Python 2

  2. REGIR REGIR Public

    A practical and scalable Gillespie Algorithm for complex non-Markovian Stochastic Simulations, with applications to systems biology.

    Python 2

  3. Ab-binding Ab-binding Public

    Identify antibodies binding the same epitope

    Python 1

  4. RA-drug-discovery RA-drug-discovery Public

    Cell-type Specific Gene Networks and Drivers in Rheumatoid Arthritis

    Python 1

  5. cdiversity cdiversity Public

    A Python library for computing clonal relationship and diversity in B cell repertoire data

    Python

  6. Raman-Imaging-Processing Raman-Imaging-Processing Public

    Provide libraries to process Hyperspectral Raman images, including batch effect correction with non cell region estimation and subtraction.

    Python 3 2

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