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...
Autores principales: | , , , , , |
---|---|
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 |