Analysis and interpretation of microarray data is not a trivial task. Many public and commercial bioinformatics tools have been developed to help scientists interpret the lists of differentially expressed genes that are the result of microarray experiments. For example, Gene Ontology and Pathway Mapping tools (1–4
) allow batch input of genes and produce lists of GO terms or pathways that are significantly correlated with the input set of genes (5–13
The outcome of these tools is based on well-established relationships between the genes and biological processes in which they participate. However, the primary literature contains much more information about the functions of genes than is captured in structured vocabularies or canonical pathways. To extract this additional information on gene function from literature, we used thesaurus-based keyword matching in Medline abstracts to link human, mouse and rat genes to biomedical concepts describing liver pathologies, pathways, GO terms, diseases, drugs and tissues (). This approach builds on the assumption that co-occurrence of a gene and a biomedical concept in the same abstract is an indication of a functional link between the gene and the concept.
Overview of the 11 thesauri that were generated to search Medline
In this article, we describe a tool named CoPub that calculates keyword over-representation for a set of regulated genes in a similar fashion to general GO term over-representation tools, but where the over-represented keywords for the gene set are retrieved directly from Medline by text mining. Several text mining methods for the analysis of microarray data have been published that annotate clustered sets of regulated genes based on their literature profile (14–17
), or on their expression profile, often based on subsets of the total Medline repository (18–21
). CoPub uses the entire Medline library to calculate robust statistics for gene-keyword co-occurrence, and is not dependent on pre-clustered gene sets to calculate significance for keyword over-representation. In addition to calculating over-represented keywords, CoPub also shows the results graphically in an interactive network, providing an additional level of insight into the biological mechanisms related to a set of regulated genes.
CoPub has two other features: the Gene search and the BioConcept search. The Gene search and the BioConcept search options identify genes and keywords that share occurrences in Medline abstracts with a gene or keyword of interest, which provides a kind of annotation for the gene or keyword of interest.
In an earlier study (22
), we successfully applied CoPub for compound toxicity evaluation of a variety of compounds, which shows that CoPub is a useful additional bioinformatics tool for microarray data analysis. CoPub is freely accessible at http://services.nbic.nl/cgi-bin/copub/CoPub.pl