National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.
Bioinformatics. 2012 May 15;28(10):1408-10. doi: 10.1093/bioinformatics/bts156. Epub 2012 Apr 6.
Progress in high-throughput genomic technologies has led to the development of a variety of resources that link genes to functional information contained in the biomedical literature. However, tools attempting to link small molecules to normal and diseased physiology and published data relevant to biologists and clinical investigators, are still lacking. With metabolomics rapidly emerging as a new omics field, the task of annotating small molecule metabolites becomes highly relevant. Our tool Metab2MeSH uses a statistical approach to reliably and automatically annotate compounds with concepts defined in Medical Subject Headings, and the National Library of Medicine's controlled vocabulary for biomedical concepts. These annotations provide links from compounds to biomedical literature and complement existing resources such as PubChem and the Human Metabolome Database.
高通量基因组技术的进步已经产生了各种资源,这些资源将基因与生物医学文献中包含的功能信息联系起来。然而,将小分子与正常和疾病生理学以及与生物学家和临床研究人员相关的已发表数据联系起来的工具仍然缺乏。随着代谢组学迅速成为一个新的组学领域,注释小分子代谢物的任务变得非常重要。我们的工具 Metab2MeSH 使用一种统计方法来可靠且自动地用 Medical Subject Headings 中定义的概念以及美国国家医学图书馆的生物医学概念受控词汇对化合物进行注释。这些注释为化合物提供了与生物医学文献的链接,并补充了 PubChem 和人类代谢组数据库等现有资源。