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Nucleic Acids Research Advance Access published online on October 11, 2007
Nucleic Acids Research, doi:10.1093/nar/gkm788
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Database issue

PubMeth: a cancer methylation database combining text-mining and expert annotation

Maté Ongenaert*, Leander Van Neste, Tim De Meyer, Gerben Menschaert, Sofie Bekaert and Wim Van Criekinge

Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Laboratory for Bioinformatics and Computational Genomics, Ghent University, B-9000 Ghent, Belgium

* To whom correspondence should be addressed. Tel: +32 9 264 99 22; Fax: +32 9 264 62 19; Email: mate.ongenaert{at}ugent.be

Received August 13, 2007. Revised September 15, 2007. Accepted September 17, 2007.

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http://www.pubmeth.org.

PubMeth is based on text-mining of Medline/PubMed abstracts, combined with manual reading and annotation of preselected abstracts. The text-mining approach results in increased speed and selectivity (as for instance many different aliases of a gene are searched at once), while the manual screening significantly raises the specificity and quality of the database. The summarized overview of the results is very useful in case more genes or cancer types are searched at the same time.


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