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Nat Genet. 2001 May;28(1):1-2.
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Nat Genet. 2001 May;28(1):9-10.
A literature network of human genes for high-throughput analysis of gene expression.
Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway.
We have carried out automated extraction of explicit and implicit biomedical knowledge from publicly available gene and text databases to create a gene-to-gene co-citation network for 13,712 named human genes by automated analysis of titles and abstracts in over 10 million MEDLINE records. The associations between genes have been annotated by linking genes to terms from the medical subject heading (MeSH) index and terms from the gene ontology (GO) database. The extracted database and accompanying web tools for gene-expression analysis have collectively been named 'PubGene'. We validated the extracted networks by three large-scale experiments showing that co-occurrence reflects biologically meaningful relationships, thus providing an approach to extract and structure known biology. We validated the applicability of the tools by analyzing two publicly available microarray data sets.
PMID: 11326270 [PubMed - indexed for MEDLINE]
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Cited by 93 PubMed Central articles
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myGRN: a database and visualisation system for the storage and analysis of developmental genetic regulatory networks.
Bacha J, Brodie JS, Loose MW.
BMC Dev Biol. 2009 Jun 6; 9:33. Epub 2009 Jun 6.
[BMC Dev Biol. 2009]
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Application of a New Probabilistic Model for Mining Implicit Associated Cancer Genes from OMIM and Medline.
Zhu S, Okuno Y, Tsujimoto G, Mamitsuka H.
Cancer Inform. 2007 Feb 25; 2:361-71. Epub 2007 Feb 25.
[Cancer Inform. 2007]
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SiPaGene: A new repository for instant online retrieval, sharing and meta-analyses of GeneChip expression data.
Menssen A, Edinger G, Grün JR, Haase U, Baumgrass R, Grützkau A, Radbruch A, Burmester GR, Häupl T.
BMC Genomics. 2009 Mar 5; 10:98. Epub 2009 Mar 5.
[BMC Genomics. 2009]
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