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 · 85
Predicting the pathogenicity of missense variants using features derived from AlphaFold2.
PMID 37084271 · PMC10203375 · Bioinformatics (Oxford, England) · 2023 · 6 claims · 8 setups
AlphaFold2-derived structural features (solvent accessibility, amino acid network features, physicochemical environment, pLDDT) can be used to train a random forest classifier (AlphScore) that distinguishes proxy-benign from proxy-pathogenic missense variants.
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CanPredict: a computational tool for predicting cancer-associated missense mutations.
PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups
CanPredict is a web application providing public access to a random forest classifier that combines SIFT, LogR.E-value, and GOSS scores to predict whether a missense mutation is cancer-associated
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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups
CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.