iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data.
作者: Ashis SahaMinji JeonAik Choon TanJaewoo Kang
刊名: PLoS ONE, 2017, Vol.10 (7)
来源数据库: Directory of Open Access Journals
DOI: 10.1371/journal.pone.0131656
原始语种摘要: Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also...
全文获取路径: DOAJ  (合作)
影响因子:3.73 (2012)

  • visualize 目视
  • Data 数据
  • understand 理解
  • community 群落
  • upload 上装
  • discover 发现
  • reliability 可靠性
  • tools 工具
  • complex 超群
  • interacting 相克的