%0 Journal Article %1 pubmeth.2007 %A Ongenaert, Maté %A Neste, Leander Van %A Meyer, Tim De %A Menschaert, Gerben %A Bekaert, Sofie %A Criekinge, Wim Van %D 2007 %J Nucleic Acids Research %K CAT CAT-DBS-DNA-mythylation CAT-ONLINE-SW CAT-REL-COOR DNA-mythylation %P 1–5 %T PubMeth: a cancer methylation database combining text-mining and expert annotation (http://www.pubmeth.org) %U http://nar.oxfordjournals.org/cgi/reprint/gkm788v2 %X 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 methyl- ated 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.

@article{pubmeth.2007, abstract = {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 methyl- ated 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.}, added-at = {2010-09-20T22:16:05.000+0200}, author = {Ongenaert, Maté and Neste, Leander Van and Meyer, Tim De and Menschaert, Gerben and Bekaert, Sofie and Criekinge, Wim Van}, biburl = {https://www.bibsonomy.org/bibtex/2b99887877a3538f3640cb72734ef3703/huiyangsfsu}, interhash = {676e45e6d6916dbf774ed62eb4a2ca99}, intrahash = {b99887877a3538f3640cb72734ef3703}, journal = {Nucleic Acids Research}, keywords = {CAT CAT-DBS-DNA-mythylation CAT-ONLINE-SW CAT-REL-COOR DNA-mythylation}, pages = {1–5 }, timestamp = {2010-11-09T08:41:30.000+0100}, title = {PubMeth: a cancer methylation database combining text-mining and expert annotation (http://www.pubmeth.org)}, url = {http://nar.oxfordjournals.org/cgi/reprint/gkm788v2}, year = 2007 }