Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Bioinformatics. 2010 Feb 15;26(4):456-63. doi: 10.1093/bioinformatics/btp683. Epub 2009 Dec 9.
The elucidation of biological concepts enriched with differentially expressed genes has become an integral part of the analysis and interpretation of genomic data. Of additional importance is the ability to explore networks of relationships among previously defined biological concepts from diverse information sources, and to explore results visually from multiple perspectives. Accomplishing these tasks requires a unified framework for agglomeration of data from various genomic resources, novel visualizations, and user functionality.
We have developed ConceptGen, a web-based gene set enrichment and gene set relation mapping tool that is streamlined and simple to use. ConceptGen offers over 20,000 concepts comprising 14 different types of biological knowledge, including data not currently available in any other gene set enrichment or gene set relation mapping tool. We demonstrate the functionalities of ConceptGen using gene expression data modeling TGF-beta-induced epithelial-mesenchymal transition and metabolomics data comparing metastatic versus localized prostate cancers.
阐明富含差异表达基因的生物学概念已成为分析和解释基因组数据不可或缺的一部分。更重要的是，能够从多个信息源探索先前定义的生物学概念之间的关系网络，并从多个角度进行可视化探索结果。完成这些任务需要一个统一的框架，用于聚合来自各种基因组资源的数据、新颖的可视化和用户功能。
我们开发了 ConceptGen，这是一种基于网络的基因集富集和基因集关系映射工具，使用起来简单流畅。ConceptGen 提供了超过 20,000 个概念，包括 14 种不同类型的生物学知识，其中包括目前任何基因集富集或基因集关系映射工具都没有的数据。我们使用基因表达数据建模 TGF-β诱导的上皮-间充质转化和代谢组学数据比较转移性和局限性前列腺癌来演示 ConceptGen 的功能。
