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).
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Has reproduction · 72
Prediction of prognostic signatures in triple-negative breast cancer based on the differential expression analysis via NanoString nCounter immune panel.
PMID 33138797 · PMC7607642 · BMC cancer · 2020 · 8 claims · 8 setups
edgeR-based DEG selection is more appropriate for feature selection than Elastic Net when sample sizes are small.
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Protocol to perform cell-type-specific transcriptome-wide association study using scPrediXcan framework.
PMID 41689808 · PMC12925207 · STAR protocols · 2026 · 6 claims · 6 setups
scPrediXcan enables cell-type-specific transcriptome-wide association studies (TWAS) by integrating deep learning-based prediction of gene expression from DNA sequence and epigenetic features.
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Has reproduction · 83
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
170 unique human AFB1 targets were identified by merging ChEMBL, SwissTargetPrediction, and PharmMapper predictions
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Has reproduction · 68
Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing.
PMID 31443728 · PMC6708158 · Genome medicine · 2019 · 6 claims · 8 setups
A near-perfect chronological age predictor can in principle be developed from DNA methylation when training sample size is sufficiently large.
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AMR-GNN: a multi-representation graph neural network framework to enable genomic antimicrobial resistance prediction.
PMID 41792137 · PMC13087051 · Nature communications · 2026 · 7 claims · 8 setups
AMR-GNN, a graph neural network integrating multiple genomic representations (unitigs, SNPs, FCGR) via low-rank multimodal fusion, improves AMR phenotype prediction in P. aeruginosa compared to single-representation baseline models.
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pmid-42120410
PMID 42120410 · PMC13168506 · 8 claims · 6 setups
DrEval is a living open-source benchmarking pipeline for unbiased, biologically meaningful evaluation of cancer drug response prediction models, integrating standardized preprocessing, hyperparameter tuning, statistically rigorous evaluation, cross-study benchmarks, and ablation studies.