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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CGMIM: automated text-mining of Online Mendelian Inheritance in Man (OMIM) to identify genetically-associated cancers and candidate genes.
PMID 15796777 · PMC1274267 · BMC bioinformatics · 2005 · 8 claims · 2 setups
CGMIM is a Perl program that text-mines OMIM entries to identify cancer-gene associations and genetically-related cancer type pairs.
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SysPIMP: the web-based systematical platform for identifying human disease-related mutated sequences from mass spectrometry.
PMID 19036792 · PMC2686442 · Nucleic acids research · 2009 · 8 claims · 7 setups
SysPIMP is a web-based platform integrating disease mutation databases with X!Tandem and BLAST to identify disease-related mutated proteins from MS results
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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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Building disease-specific drug-protein connectivity maps from molecular interaction networks and PubMed abstracts.
PMID 19649302 · PMC2709445 · PLoS computational biology · 2009 · 7 claims · 4 setups
A computational framework can build disease-specific drug-protein connectivity maps by integrating protein interaction networks and PubMed literature mining, without gene expression profiles from drug perturbation experiments
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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.