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DiseaseMeth version 2.0: a major expansion and update of the human disease methylation database.

The human disease methylation database (DiseaseMeth,  http://bioinfo.hrbmu.edu.cn/diseasemeth/ ) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microa... Full description

Journal Title: Nucleic acids research January 4, 2017, Vol.45, pp.D888-D895
Main Author: Xiong, Yichun
Other Authors: Wei, Yanjun , Gu, Yue , Zhang, Shumei , Lyu, Jie , Zhang, Bin , Chen, Chuangeng , Zhu, Jiang , Wang, Yihan , Liu, Hongbo , Zhang, Yan
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: E-ISSN: 1362-4962 ; DOI: 10.1093/nar/gkw1123
Link: http://search.proquest.com/docview/1845248018/?pq-origsite=primo
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title: DiseaseMeth version 2.0: a major expansion and update of the human disease methylation database.
format: Article
creator:
  • Xiong, Yichun
  • Wei, Yanjun
  • Gu, Yue
  • Zhang, Shumei
  • Lyu, Jie
  • Zhang, Bin
  • Chen, Chuangeng
  • Zhu, Jiang
  • Wang, Yihan
  • Liu, Hongbo
  • Zhang, Yan
subjects:
  • Computational Biology–Methods
  • DNA Methylation–Methods
  • Databases, Genetic–Methods
  • Epigenomics–Methods
  • Gene Expression Profiling–Methods
  • Genetic Association Studies–Methods
  • Humans–Methods
  • Search Engine–Methods
  • Software–Methods
  • Web Browser–Methods
ispartof: Nucleic acids research, January 4, 2017, Vol.45, pp.D888-D895
description: The human disease methylation database (DiseaseMeth,  http://bioinfo.hrbmu.edu.cn/diseasemeth/ ) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease–gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease–gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease–disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.
language: eng
source:
identifier: E-ISSN: 1362-4962 ; DOI: 10.1093/nar/gkw1123
fulltext: fulltext
issn:
  • 13624962
  • 1362-4962
url: Link


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titleDiseaseMeth version 2.0: a major expansion and update of the human disease methylation database.
creatorXiong, Yichun ; Wei, Yanjun ; Gu, Yue ; Zhang, Shumei ; Lyu, Jie ; Zhang, Bin ; Chen, Chuangeng ; Zhu, Jiang ; Wang, Yihan ; Liu, Hongbo ; Zhang, Yan
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identifierE-ISSN: 1362-4962 ; DOI: 10.1093/nar/gkw1123
subjectComputational Biology–Methods ; DNA Methylation–Methods ; Databases, Genetic–Methods ; Epigenomics–Methods ; Gene Expression Profiling–Methods ; Genetic Association Studies–Methods ; Humans–Methods ; Search Engine–Methods ; Software–Methods ; Web Browser–Methods
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descriptionThe human disease methylation database (DiseaseMeth,  http://bioinfo.hrbmu.edu.cn/diseasemeth/ ) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease–gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease–gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease–disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.
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