AI in Oncology · AI Models

The largest real-world clinical sequencing registry in oncology — the place to test whether a variant-effect or biomarker model generalises beyond TCGA.

Proteogenomic companion to TCGA: the largest public set where protein-level measurements, genomics and images exist for the same tumours.

Public map of cancer vulnerabilities in cell lines — the training and validation ground for target-discovery and drug-response models.

A public benchmark resource run by NIST within a consortium of public bodies, companies and academic centres. It contains seven thoroughly characterised human genomes with benchmark variant sets and high-confidence regions, and is used to measure how accurately a bioinformatics pipeline calls variants. It is not an oncology dataset and not an imaging dataset — it is a reference point for genome readout itself. The consortium works with the GA4GH Benchmarking Team on comparison standards. Distribution: the NIST reference material shop, the Coriell Institute and the Personal Genome Project.

The naming authority for HLA alleles: the catalogue whose size — thirty thousand names against roughly a hundred well-measured alleles — defines the central problem of this field.

The reference multi-omics cancer cohort: molecular profiles, clinical outcomes and whole-slide images for 33 cancer types, downloadable through the GDC portal and API.