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 · 79
Computationally scalable regression modeling for ultrahigh-dimensional omics data with ParProx.
PMID 34254998 · PMC8575036 · Briefings in bioinformatics · 2021 · 6 claims · 4 setups
ParProx implements overlapping and non-overlapping (latent) group lasso regression for time-to-event (Cox) and classification (logistic) analysis with variables grouped by biological priors.
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Bayesian survival analysis in genetic association studies.
PMID 18617538 · PMC2530885 · Bioinformatics (Oxford, England) · 2008 · 7 claims · 5 setups
A novel Bayesian method (BETA-Surv) extends prior case-control haplotype-clustering work to censored survival outcomes by clustering haplotypes via gene tree/perfect phylogeny topology and relative mutation age.
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The androgen receptor CAG repeat polymorphism and modification of breast cancer risk in BRCA1 and BRCA2 mutation carriers.
PMID 15743497 · PMC1064126 · Breast cancer research : BCR · 2005 · 7 claims · 5 setups
The AR CAG repeat polymorphism does not modify breast cancer risk in BRCA1 mutation carriers
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Has reproduction · 85
Digital sorting of complex tissues for cell type-specific gene expression profiles.
PMID 23497278 · PMC3626856 · BMC bioinformatics · 2013 · 8 claims · 8 setups
The Digital Sorting Algorithm (DSA) deconvolves mixed tissue expression into cell type-specific profiles using only marker genes, without requiring prior knowledge of cell type frequencies or in vitro pure-cell profiles.
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Has reproduction · 44
Detecting DNA modifications from SMRT sequencing data by modeling sequence context dependence of polymerase kinetic.
PMID 23516341 · PMC3597545 · PLoS computational biology · 2013 · 8 claims · 7 setups
Local sequence context strongly determines position-specific polymerase kinetic rate: roughly 80% of IPD variation is explained by a 10 bp context (7 bases upstream, 2 bases downstream of the incorporation site), saturating at 7 bases upstream.