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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Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays.
PMID 16549007 · PMC1544357 · BMC bioinformatics · 2006 · 7 claims · 2 setups
A methodology combining Cox proportional hazards models with a compound covariate, cross-validated log partial likelihood (ACVL) for predictive accuracy, and permutation-based significance testing can identify an optimal subset of significant genes for survival prediction
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Has reproduction · 53
Molecular Biomarker of Drug Resistance Developed From Patient-Derived Organoids Predicts Survival of Colorectal Cancer Patients.
PMID 35425715 · PMC9004628 · Frontiers in oncology · 2022 · 8 claims · 7 setups
Patient-derived colorectal cancer organoids (CRCOs) can be established from surgical CRC tissue with an 82% success rate (41/50)
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Mutant, wild type, or overall p53 expression: freedom from clinical progression in tumours of astrocytic lineage.
PMID 15494720 · PMC2409947 · British journal of cancer · 2004 · 8 claims · 7 setups
Significant overexpression of p53 protein was found in 48% of 74 astrocytic tumours
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Family history of breast cancer and all-cause mortality after breast cancer diagnosis in the Breast Cancer Family Registry.
PMID 19034644 · PMC2728159 · Breast cancer research and treatment · 2009 · 7 claims · 5 setups
Family history of breast cancer is not associated with all-cause mortality after breast cancer diagnosis in women without a known germline BRCA1/BRCA2 mutation.
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Has reproduction · 91
A reference profile-free deconvolution method to infer cancer cell-intrinsic subtypes and tumor-type-specific stromal profiles.
PMID 32111252 · PMC7049190 · Genome medicine · 2020 · 8 claims · 8 setups
DeClust is a reference profile-free deconvolution method that simultaneously deconvolves bulk tumor expression into cancer, immune, and stromal compartments and clusters samples into cancer cell-intrinsic molecular subtypes, outputting subtype-specific reference profiles for the cohort rather than for individuals.