Minguez Pablo, Al-Shahrour Fátima, Montaner David, Dopazo Joaquín
Department of Bioinformatics and Functional Genomics Node, (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, E46013, Spain.
Bioinformatics. 2007 Nov 15;23(22):3098-9. doi: 10.1093/bioinformatics/btm445. Epub 2007 Sep 13.
The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.
微阵列技术的日益广泛应用,使得对结果进行功能解读的方法也有了相应需求。除了基因的传统功能注释,如基因本体、通路等,其他信息来源仍有待挖掘。文本挖掘方法能够提取具有不同功能、化学、临床等意义的信息性术语(生物实体),这些术语可与基因相关联。我们展示了如何在合适的统计框架内利用这些关联,以及如何通过易于使用的基于网络的环境将其应用于微阵列实验的功能解读。还介绍了使用生物实体进行的功能富集和基因集富集测试。