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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Association of MUTYH and colorectal cancer.
PMID 16804517 · PMC2360610 · British journal of cancer · 2006 · 7 claims · 3 setups
Bi-allelic MUTYH mutations confer a very large increase in colorectal cancer risk (GRR=117), supporting a causal role in colorectal cancer
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Understanding genetic epidemiologic association studies Part 1: fundamentals.
PMID 19962167 · PMC2843757 · Surgery · 2010 · 8 claims · 3 setups
Genetic epidemiology aims to establish whether a disease has a genetic component while accounting for environmental influences.
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Heterogeneity of p53 mutational status in intramucosal carcinoma of the colorectum.
PMID 11223545 · PMC5926696 · Japanese journal of cancer research : Gann · 2001 · 7 claims · 4 setups
p53 gene mutations occur and diverge at the intramucosal carcinoma stage, before submucosal invasion
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Association between cigarette smoking, APC mutations and the risk of developing sporadic colorectal adenomas and carcinomas.
PMID 16545110 · PMC1475604 · BMC cancer · 2006 · 8 claims · 4 setups
Smoking is associated with adenoma and CRC development, with the association strongest in tumors lacking APC truncation mutations
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Mutational inactivation of mitotic checkpoint genes, hsMAD2 and hBUB1, is rare in sporadic digestive tract cancers.
PMID 10543255 · PMC5926140 · Japanese journal of cancer research : Gann · 1999 · 6 claims · 4 setups
Mutation of the hsMAD2 gene was not observed in any of the 32 sporadic digestive tract cancers examined.
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Has reproduction · 71
Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer.
PMID 30993001 · PMC6459838 · NPJ systems biology and applications · 2019 · 8 claims · 7 setups
Retaining only the top ~3 most correlated edges per gene (EPG3) combined with FastUnfold clustering (termed PGCNA) produces gene co-expression modules with significantly better separation and enrichment of known biology than using all edges or other clustering methods.