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).

• Speeding disease gene discovery by sequence based candidate prioritization.

  PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups

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  Disease genes (OMIM) differ significantly from non-disease genes in sequence-based features including gene/cDNA/protein size, exon number, homolog conservation, secretion signal, 3' UTR length, CpG islands, and distance to nearest gene.

  ensembl training same hgmd comparative machine tenfold

• 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

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  CGMIM is a Perl program that text-mines OMIM entries to identify cancer-gene associations and genetically-related cancer type pairs.

  omim automated manual

• POCUS: mining genomic sequence annotation to predict disease genes.

  PMID 14611661 · PMC329128 · Genome biology · 2003 · 8 claims · 6 setups

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  Genes predisposing to the same disease tend to share functional annotation IDs (GO/InterPro) more than expected by chance

  omim genome disease comparative pocus expression-id

• Commonality of functional annotation: a method for prioritization of candidate genes from genome-wide linkage studies.

  PMID 18263617 · PMC2275105 · Nucleic acids research · 2008 · 8 claims · 7 setups

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  Genes correlated with a common complex trait are more likely to share GO functional annotations than genes not correlated with that trait

  genes candidate simulated alzheimer's genome-wide term null-hypothesis

• Integration of text- and data-mining using ontologies successfully selects disease gene candidates.

  PMID 15767279 · PMC1065256 · Nucleic acids research · 2005 · 7 claims · 6 setups

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  Integrating eVOC anatomical ontology-based text-mining of PubMed abstracts with data-mining of gene expression annotation successfully selects and prioritizes candidate disease genes

  biomedical refseq training independent text-mining data-mining candidate

• Functional annotation and identification of candidate disease genes by computational analysis of normal tissue gene expression data.

  PMID 18560577 · PMC2409962 · PloS one · 2008 · 7 claims · 5 setups

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  Ranked Coexpression Groups (RCG) built from k=6 nearest coexpressed genes, combined with a majority-rule functional characterization, integrate multiple datasets/coexpression measures to generate high-confidence functional annotation predictions

  normal genome-wide same omim microarray sage computational