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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Organization of physical interactomes as uncovered by network schemas.
PMID 18949022 · PMC2561054 · PLoS computational biology · 2008 · 7 claims · 5 setups
A computational procedure can systematically identify 'emergent' network schemas that are both recurrent and over-represented relative to randomized networks preserving lower-order subschema distributions
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Gene-disease relationship discovery based on model-driven data integration and database view definition.
PMID 19042916 · PMC2639000 · Bioinformatics (Oxford, England) · 2009 · 8 claims · 4 setups
Explicit gene–disease relationships can be formulated as candidate gene definitions (e.g., co-localization, dysregulation, functional similarity) that may include intermediary orthologous or interacting genes
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Network of Cancer Genes: a web resource to analyze duplicability, orthology and network properties of cancer genes.
PMID 19906700 · PMC2808873 · Nucleic acids research · 2010 · 7 claims · 4 setups
NCG is a web database integrating duplicability, orthology, evolutionary appearance, and network topology data for 736 human cancer genes
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Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks.
PMID 18782832 · PMC2686584 · Nucleic acids research · 2009 · 8 claims · 5 setups
CTD is a manually curated knowledgebase that integrates chemical-gene interactions, chemical-disease relationships, and gene-disease relationships into a chemical-gene-disease triad
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Computational verification of protein-protein interactions by orthologous co-expression.
PMID 15740634 · PMC555590 · BMC bioinformatics · 2005 · 7 claims · 8 setups
Co-expression of orthologous protein pairs across multiple species can verify/predict S. cerevisiae PPIs with better performance than S. cerevisiae co-expression alone.