A literature network of human genes for high-throughput analysis of gene expression View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2001-05

AUTHORS

Tor-Kristian Jenssen, Astrid Lægreid, Jan Komorowski, Eivind Hovig

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. More... »

PAGES

21

References to SciGraph publications

Journal

TITLE

Nature Genetics

ISSUE

1

VOLUME

28

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ng0501-21

    DOI

    http://dx.doi.org/10.1038/ng0501-21

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1005323022

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/11326270


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