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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Integration of text- and data-mining using ontologies successfully selects disease gene candidates.
PMID 15767279 · PMC1065256 · Nucleic acids research · 2005 · 7 claims · 6 setups
Integrating eVOC anatomical ontology-based text-mining of PubMed abstracts with data-mining of gene expression annotation successfully selects and prioritizes candidate disease genes
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Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome.
PMID 15892868 · PMC1175952 · Genome biology · 2005 · 8 claims · 6 setups
Two quantitative benchmarks (functional-annotation-based and physical-interaction-based log likelihood ratio scores) can measure relative accuracy of human PPI datasets
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QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL.
PMID 16381937 · PMC1347390 · Nucleic acids research · 2006 · 8 claims · 5 setups
QTL MatchMaker integrates QTL information with physical, genetic and cytogenetic maps across human, mouse and rat genomes
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Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.
PMID 16757574 · PMC1475747 · Nucleic acids research · 2006 · 6 claims · 8 setups
Applying seven independent computational disease-gene prioritization methods in concert to 9556 positional candidate genes identifies a prioritized set of likely T2D and obesity candidate genes
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Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network.
PMID 19728866 · PMC2768980 · Genome biology · 2009 · 6 claims · 6 setups
Integrating 16 genomic features (32 sub-features) via a naïve Bayes classifier produces a genome-scale FLN of 21,657 human genes and 22,388,609 weighted links that outperforms any individual data source for inferring functional linkages.