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).

• Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature.

  PMID 35143511 · PMC8830616 · PloS one · 2022 · 8 claims · 6 setups

  Has reproduction · 48

  A hybrid signature combining the Nottingham Prognostic Index with SIS-selected gene expressions can be built in a data-driven fashion (NPI treated as a gene expression during feature selection).

  metabric scan-b gene rna-seq feature

• 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

• Construction and Validation of an Immune Infiltration-Related Gene Signature for the Prediction of Prognosis and Therapeutic Response in Breast Cancer.

  PMID 33986754 · PMC8110914 · Frontiers in immunology · 2021 · 7 claims · 8 setups

  Has reproduction · 51

  A 15-gene immune infiltration-related signature (IRS) predicts overall survival in breast cancer, with higher IRS indicating worse prognosis

  tcga metabric geo breast immune bulk microarray

• DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data.

  PMID 34261540 · PMC8281595 · Genome medicine · 2021 · 6 claims · 7 setups

  Has reproduction · 84

  DeepProg, an ensemble of deep-learning and machine-learning models, robustly predicts patient survival subtypes from multi-omics data and explicitly models survival as the objective while predicting new patient risks

  tcga breast metabric brca bulk mirna methylation

• Integrating multi-omics data reveals the antitumor role and clinical benefits of gamma-delta T cells in triple-negative breast cancer.

  PMID 40197136 · PMC11974128 · BMC cancer · 2025 · 8 claims · 8 setups

  Has reproduction · 59

  High γδT cell infiltration is associated with favorable prognosis in TNBC but not in HR-positive or HER2-positive breast cancer

  tnbc tcga-brca metabric single-cell bulk immunohistochemistry

• A metadata approach for clinical data management in translational genomics studies in breast cancer.

  PMID 19948017 · PMC3225860 · BMC medical genomics · 2009 · 8 claims · 5 setups

  Full-text index only

  A metadata/CDE-based approach using CancerGrid's semantic web tools enables automatic integration of heterogeneous clinical datasets without loss of original detail

  clinical breast metadata estrogen her2