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. 2008 Jul 1;36(Web Server issue):W406-10.
doi: 10.1093/nar/gkn215. Epub 2008 Apr 28.

CoPub: a literature-based keyword enrichment tool for microarray data analysis

Raoul Frijters  1 , Bart Heupers, Pieter van Beek, Maurice Bouwhuis, René van Schaik, Jacob de Vlieg, Jan Polman, Wynand Alkema
Affiliations

CoPub: a literature-based keyword enrichment tool for microarray data analysis

Raoul Frijters et al. Nucleic Acids Res. .

Abstract

Medline is a rich information source, from which links between genes and keywords describing biological processes, pathways, drugs, pathologies and diseases can be extracted. We developed a publicly available tool called CoPub that uses the information in the Medline database for the biological interpretation of microarray data. CoPub allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs. CoPub is freely accessible at http://services.nbic.nl/cgi-bin/copub/CoPub.pl.

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Figures

Figure 1.
Figure 1.
Screenshots and workflow of the Microarray data analysis. (A) Input screen for uploading gene identifiers (Affymetrix probe set identifiers, Entrez Gene identifiers or Ensembl identifiers), selection of keyword categories and to specify thresholds (e.g. P-value significance level), with which the keyword over-representation analysis will be performed (sensible defaults are provided). (B) Output screen which reports on significantly linked keywords to the set of submitted genes, ranked on P-values after multiple testing correction. The number of genes that are significantly associated with the analyzed keyword, links to an overview of uploaded genes that share co-publications with the analyzed keyword (C), which provides access to highlighted Medline abstracts in which they co-occur (D). (E) Visualization of the keyword over-representation results in an interactive literature network (as SVG), in which nodes represent genes and keywords, and edges represent links in Medline abstracts. Clicking on an edge retrieves highlighted Medline abstracts in which genes and keywords co-occur (D).
Figure 2.
Figure 2.
Screenshots and workflows of the Gene search (A) and the BioConcept search (B). (A1) Input screen of the Gene search, which requires a single gene name as input. Furthermore, the categories of keywords need to be specified for which co-occurrences in literature with the gene of interest will be matched and retrieved. (A2) Output screen of the Gene search, which reports on the number of keywords that co-occur with the gene of interest, and links to an overview of the keywords (A3) and to Medline abstracts in which they co-occur (A4). (B1) Input screen of the BioConcept search, which requires a single keyword as input. (B2) Page to specify the categories of genes and keywords for which co-occurrences in literature with the keyword of interest will be matched and retrieved. (B3) Output screen of the BioConcept search, which reports on genes and keywords that co-occur with the keyword of interest in Medline abstracts, and with links to these abstracts (B4).
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