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 · 80
Differential analysis of RNA structure probing experiments at nucleotide resolution: uncovering regulatory functions of RNA structure.
PMID 35869080 · PMC9307511 · Nature communications · 2022 · 7 claims · 4 setups
DiffScan is a computational framework combining a Normalization module and a Scan module to identify SVRs at nucleotide resolution from SP data.
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Negative emotionality: monoamine oxidase B gene variants modulate personality traits in healthy humans.
PMID 19657584 · PMC3653168 · Journal of neural transmission (Vienna, Austria : 1996) · 2009 · 7 claims · 7 setups
MAOB SNPs rs10521432 and rs6651806 are significantly associated with Negative Emotionality in healthy volunteers
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Has reproduction
Using random walks to identify cancer-associated modules in expression data.
PMID 24128261 · PMC4015830 · BioData mining · 2013 · 8 claims · 8 setups
Walktrap-GM, a random-walk community detection algorithm adapted with stopping criteria (maximum modularity, maximum size, maximum module score), identifies modules significantly enriched with cancer genes in expression-weighted interaction networks.
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PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size.
PMID 16620382 · PMC1459209 · BMC bioinformatics · 2006 · 7 claims · 3 setups
PedGenie is a valid, flexible statistical tool for genetic association analysis in pedigrees of arbitrary size and structure using Monte Carlo significance testing
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A statistical model to identify differentially expressed proteins in 2D PAGE gels.
PMID 19763172 · PMC2734266 · PLoS computational biology · 2009 · 7 claims · 5 setups
A mixture likelihood model incorporating both detected and non-detected proteins has higher statistical power to detect differential expression than standard approaches like the Student's t-test.