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Probably Learning!
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Probably Learning!
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Achievement: Pull Shark

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@chiralbd @deepbioacademy

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hossainlab/README.md

Bio

I am a bioinformatics scientist with a track record of building and deploying reproducible multi-omics frameworks to decode the molecular architecture of cancer and neurological diseases. My research interests three interconnected domains: (1) Integrative analysis of bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics identify robust immunological biomarkers and therapeutic targets within tumor microenvironments. (2) Deep learning applications in single-cell genomics (data integration, celltype annotation)

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  1. salmon-rnaseq salmon-rnaseq Public

    End-to-end bulk RNA-seq quantification pipeline using Salmon and SRA-Tools

    R 1

  2. fezf2-multiomics fezf2-multiomics Public

    Mechanisms of Fezf2 mutation in cortical development and identification of therapeutic targets

    Jupyter Notebook 1

  3. GBM-Transcriptomic-MetaAnalysis GBM-Transcriptomic-MetaAnalysis Public

    GBM Transcriptomic Meta-Analysis

    HTML 1

  4. sc-workflow sc-workflow Public

    Single-Cell Analysis Workflow

    Python 1

  5. tme-cell-state-annotation-benchmark tme-cell-state-annotation-benchmark Public

    Can General Annotation Tools Correctly Identify Functional States of Non-Malignant Cells in the Tumour Microenvironment?

    Python

  6. amr_drug_repurposing amr_drug_repurposing Public

    Deep learning-driven AMR drug repurposing using ChEMBL resistance phenotypes

    Jupyter Notebook