Cargando…

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

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 extr...

Descripción completa

Detalles Bibliográficos
Autores principales: Ongenaert, Maté, Van Neste, Leander, De Meyer, Tim, Menschaert, Gerben, Bekaert, Sofie, Van Criekinge, Wim
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2238841/
https://www.ncbi.nlm.nih.gov/pubmed/17932060
http://dx.doi.org/10.1093/nar/gkm788
_version_ 1782150472490024960
author Ongenaert, Maté
Van Neste, Leander
De Meyer, Tim
Menschaert, Gerben
Bekaert, Sofie
Van Criekinge, Wim
author_facet Ongenaert, Maté
Van Neste, Leander
De Meyer, Tim
Menschaert, Gerben
Bekaert, Sofie
Van Criekinge, Wim
author_sort Ongenaert, Maté
collection PubMed
description 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.
format Text
id pubmed-2238841
institution National Center for Biotechnology Information
language English
publishDate 2008
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-22388412008-02-12 PubMeth: a cancer methylation database combining text-mining and expert annotation Ongenaert, Maté Van Neste, Leander De Meyer, Tim Menschaert, Gerben Bekaert, Sofie Van Criekinge, Wim Nucleic Acids Res Articles 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. Oxford University Press 2008-01 2007-10-11 /pmc/articles/PMC2238841/ /pubmed/17932060 http://dx.doi.org/10.1093/nar/gkm788 Text en © 2007 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ 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.
spellingShingle Articles
Ongenaert, Maté
Van Neste, Leander
De Meyer, Tim
Menschaert, Gerben
Bekaert, Sofie
Van Criekinge, Wim
PubMeth: a cancer methylation database combining text-mining and expert annotation
title PubMeth: a cancer methylation database combining text-mining and expert annotation
title_full PubMeth: a cancer methylation database combining text-mining and expert annotation
title_fullStr PubMeth: a cancer methylation database combining text-mining and expert annotation
title_full_unstemmed PubMeth: a cancer methylation database combining text-mining and expert annotation
title_short PubMeth: a cancer methylation database combining text-mining and expert annotation
title_sort pubmeth: a cancer methylation database combining text-mining and expert annotation
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2238841/
https://www.ncbi.nlm.nih.gov/pubmed/17932060
http://dx.doi.org/10.1093/nar/gkm788
work_keys_str_mv AT ongenaertmate pubmethacancermethylationdatabasecombiningtextminingandexpertannotation
AT vannesteleander pubmethacancermethylationdatabasecombiningtextminingandexpertannotation
AT demeyertim pubmethacancermethylationdatabasecombiningtextminingandexpertannotation
AT menschaertgerben pubmethacancermethylationdatabasecombiningtextminingandexpertannotation
AT bekaertsofie pubmethacancermethylationdatabasecombiningtextminingandexpertannotation
AT vancriekingewim pubmethacancermethylationdatabasecombiningtextminingandexpertannotation