Experiments

Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).

• Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning.

  PMID 34575658 · PMC8472680 · Journal of personalized medicine · 2021 · 6 claims · 4 setups

  Has reproduction · 86

  A training gene set of 719 unique upregulated DEGs (subtype-specific) can be used to build ML models that classify TNBC into BLIA, BLIS, MES, and LAR subtypes.

  known tnbc unique unknown gene machine term

• Integrative transcriptomic and machine learning framework reveals candidate genes and potential mechanisms of aflatoxin B1 exposure in breast cancer.

  PMID 41688730 · PMC12982753 · Scientific reports · 2026 · 7 claims · 8 setups

  Has reproduction · 83

  Twenty-two genes lie at the intersection of AFB1-predicted targets and breast cancer-associated co-expression modules/DEGs

  afb1 breast training candidate computational bulk weighted

• Elucidating the Prognostic and Therapeutic Implications of Insulin Resistance Genes in Breast Cancer: A Machine Learning-Powered Analysis.

  PMID 40427728 · PMC12109394 · Biology · 2025 · 8 claims · 8 setups

  Has reproduction · 84

  A seven-gene IRG prognostic signature (LIFR, EZR, TBC1D4, NSF, RPL5, SAA1, PGK1) predicts overall survival in breast cancer across training and four validation cohorts

  tcga-brca triple-negative ffpe bulk univariate kaplan-meier