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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Linkage disequilibrium mapping of a breast cancer susceptibility locus near RAI/PPP1R13L/iASPP.
PMID 18588689 · PMC2474586 · BMC medical genetics · 2008 · 8 claims · 6 setups
A region spanning the gene RAI and the 5' portion of XPD is associated with postmenopausal breast cancer
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Has reproduction · 83
Analyzing biomarker discovery: Estimating the reproducibility of biomarker sets.
PMID 35901020 · PMC9333302 · PloS one · 2022 · 8 claims · 6 setups
Non-reproducibility is a common problem in biomarker discovery: independently derived biomarker sets for the same phenotype frequently share very few features across studies
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Mutation analysis of the MSMB gene in familial prostate cancer.
PMID 19997100 · PMC2816656 · British journal of cancer · 2010 · 8 claims · 5 setups
No deleterious mutations were found in the MSMB coding region in 192 familial prostate cancer cases
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Discovery and characterization of gene-by-environment and epistatic genetic effects in a vertebrate model.
PMID 41672067 · PMC13174225 · Cell genomics · 2026 · 7 claims · 7 setups
A segregation analysis in an F2 medaka cross identified 16 QTLs linked to embryonic heart rate variation across temperatures
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CanSig Benchmarks Methods for Reproducible Cancer Cell State Discovery from Single-Cell Transcriptomic Data.
PMID 41231245 · PMC13053056 · Cancer research · 2026 · 7 claims · 7 setups
CanSig is a comprehensive benchmarking tool for evaluating computational methods that identify shared transcriptional signatures in cancer from scRNA-seq data
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Automatic discovery of cross-family sequence features associated with protein function.
PMID 16409628 · PMC1395344 · BMC bioinformatics · 2006 · 8 claims · 6 setups
A self-supervised data mining approach can find relationships between sequence features and functional annotations without preconceived functional categories.