Checkpoint Inhibitor & Immuno-Oncology Investigation Using Curated High-Quality Public Omics Data

Описание: Checkpoint Inhibitor & Immuno-Oncology Investigation Using Curated High-Quality Public Omics Data

Harness curated, high-quality public omics datasets to accelerate checkpoint inhibitor and immuno-oncology research. This video walks through data sourcing, QC and harmonization, biomarker discovery, response prediction models, and translational insights that link multi-omics signals to clinical outcomes in cancer immunotherapy.

📌 What’s Covered:

Overview of checkpoint pathways (PD-1/PD-L1, CTLA-4) and IO study design

Finding and curating public omics (TCGA, GEO, SRA, CPTAC, dbGaP)

QC, batch correction, and metadata harmonization

Differential expression, pathway/GSEA, TME deconvolution

Neoantigen & TCR/BCR signals, mutational/immune signatures

Building response prediction models and validating biomarkers

Reproducibility, FAIR data, and ethical/data-sharing best practices

#CheckpointInhibitors #ImmunoOncology #OmicsData #CancerImmunotherapy #Bioinformatics #PublicDatasets #TranslationalResearch #BiomarkerDiscovery #PrecisionOncology #SystemsImmunology

checkpoint inhibitor research, immuno-oncology analytics, public omics datasets, TCGA analysis, GEO RNA-seq, tumor microenvironment deconvolution, PD-1 PD-L1 CTLA-4, biomarker discovery, response prediction models, cancer immunotherapy bioinformatics, multi-omics integration, batch correction combat, differential expression GSEA, neoantigen prediction, immune signatures, precision oncology, reproducible research, data curation, clinical outcome association, translational bioinformatics