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).

• 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

• Systematic annotation of orphan RNAs reveals blood-accessible molecular barcodes of cancer identity and cancer-emergent oncogenic drivers.

  PMID 41579861 · PMC12923976 · Cell reports. Medicine · 2026 · 8 claims · 8 setups

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  oncRNA binary presence-absence patterns constitute digital molecular barcodes that capture cancer type and subtype identity

  tcga exrna cptac mda-mb-231 small machine atac-seq

• Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.

  PMID 26538066 · PMC4634735 · BMC medical genomics · 2015 · 8 claims · 7 setups

  Has reproduction · 83

  A multigene expression biomarker from PBMCs accurately classifies familial breast cancer (FBC) status

  pbmcs utah blood normal microarray svm-rfe svm

• miRge 2.0 for comprehensive analysis of microRNA sequencing data.

  PMID 30153801 · PMC6112139 · BMC bioinformatics · 2018 · 8 claims · 6 setups

  Has reproduction · 89

  An SVM-based novel miRNA detection model achieves an average MCC of 0.939 across 32 human cell datasets and outperforms miRDeep2 and miRAnalyzer on phylogenetic conservation of predicted miRNAs

  unmapped pooled colon adipose small novel a-to-i

• Exploring phenotype-related single-cells through attention-enhanced representation learning.

  PMID 41566378 · PMC12906058 · Genome medicine · 2026 · 6 claims · 5 setups

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  scPhase, an attention-based multiple instance learning (AMIL) framework with Mixture-of-Experts aggregation, predicts sample-level clinical phenotypes from raw scRNA-seq data and generalizes across patient cohorts

  pbmcs brain tumor scrna-seq