A literature network of human genes for high-throughput analysis of gene expression.

@article{citeulike:139974, abstract = {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.}, address = {Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway.}, author = {Jenssen, T. K. and Laegreid, A. and Komorowski, J. and Hovig, E. }, citeulike-article-id = {139974}, doi = {http://dx.doi.org/10.1038/88213}, issn = {1061-4036}, journal = {Nat Genet}, keywords = {diplomarbeit}, month = {May}, number = {1}, pages = {21--28}, posted-at = {2008-07-13 22:26:29}, priority = {2}, title = {A literature network of human genes for high-throughput analysis of gene expression.}, url = {http://dx.doi.org/10.1038/88213}, volume = {28}, year = {2001} }

TY - JOUR ID - citeulike:139974 L3 - citeulike-article-id:139974 N2 - 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. IS - 1 JF - Nat Genet SN - 1061-4036 AD - Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway. EP - 28 TI - A literature network of human genes for high-throughput analysis of gene expression. VL - 28 SP - 21 KW - diplomarbeit AU - Jenssen, TK AU - Laegreid, A AU - Komorowski, J AU - Hovig, E PY - 2001/05// UR - http://dx.doi.org/10.1038/88213 ER -