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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The diagnosis and management of pre-invasive breast disease: promise of new technologies in understanding pre-invasive breast lesions.
PMID 14580250 · PMC314415 · Breast cancer research : BCR · 2003 · 8 claims · 8 setups
ADH and ductal carcinoma in situ (DCIS) are precursor lesions molecularly similar to adjacent invasive breast cancer
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In silico analysis of missense substitutions using sequence-alignment based methods.
PMID 18951440 · PMC3431198 · Human mutation · 2008 · 8 claims · 7 setups
Carefully validated PMSA-based computational algorithms can achieve predictive values of ~75-95% for classifying missense substitutions as pathogenic or neutral.
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Magnetically assisted DNA assays: high selectivity using conjugated polymers for amplified fluorescent transduction.
PMID 15905472 · PMC1131937 · Nucleic acids research · 2005 · 8 claims · 8 setups
Introducing streptavidin-coated magnetic microparticles (MMPs) into a sandwich-type CP-based DNA sensor significantly improves selectivity against non-cognate DNA compared with previously reported CP-amplified sensors.
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An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases.
PMID 19091018 · PMC2638159 · BMC bioinformatics · 2008 · 6 claims · 5 setups
Existing SNP/disease databases are fragmented; no combined resource widely supports gene-, SNP-, and disease-related information together