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Bioinformatics Advance Access originally published online on May 26, 2005
Bioinformatics 2005 21(15):3324-3326; doi:10.1093/bioinformatics/bti503
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Published by Oxford University Press 2005

MeSHer: identifying biological concepts in microarray assays based on PubMed references and MeSH terms

Amira Djebbari 1,2, Svetlana Karamycheva 1, Eleanor Howe 5 and John Quackenbush 1,3,4,5,*

1The Institute for Genomic Research 9712 Medical Center Drive, Rockville, MD 20850, USA
2Department of Computer Science, The George Washington University Washington, DC, USA
3Department of Biochemistry, The George Washington University Washington, DC, USA
4Department of Statistics, Bloomberg School of Public Health, The Johns Hopkins University Baltimore, MD, USA
5Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute Boston, MA, USA

*To whom correspondence should be addressed.

Summary: MeSHer uses a simple statistical approach to identify biological concepts in the form of Medical Subject Headings (MeSH terms) obtained from the PubMed database that are significantly overrepresented within the identified gene set relative to those associated with the overall collection of genes on the underlying DNA microarray platform. As a demonstration, we apply this approach to gene lists acquired from a published study of the effects of angiotensin II (Ang II) treatment on cardiac gene expression and demonstrate that this approach can aid in the interpretation of the resulting ‘significant’ gene set.

Availability: The software is available at http://www.tm4.org

Contact: johnq{at}jimmy.harvard.edu

Supplementary information: Results from the analysis of significant genes from the published Ang II study.

Received on April 4, 2005; revised on May 16, 2005; accepted on May 16, 2005

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