Emmert-Streib Frank
Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA.
J Comput Biol. 2007 Sep;14(7):961-72. doi: 10.1089/cmb.2007.0041.
In this paper, we introduce a method to detect pathological pathways of a disease. We aim to identify biological processes rather than single genes affected by the chronic fatigue syndrome (CFS). So far, CFS has neither diagnostic clinical signals nor abnormalities that could be diagnosed by laboratory examinations. It is also unclear if the CFS represents one disease or can be subdivided in different categories. We use information from clinical trials, the gene ontology (GO) database as well as gene expression data to identify undirected dependency graphs (UDGs) representing biological processes according to the GO database. The structural comparison of UDGs of sick versus non-sick patients allows us to make predictions about the modification of pathways due to pathogenesis.
在本文中,我们介绍了一种检测疾病病理途径的方法。我们旨在识别生物过程,而非受慢性疲劳综合征(CFS)影响的单个基因。到目前为止,CFS既没有诊断性临床信号,也没有可通过实验室检查诊断出的异常情况。CFS是代表一种疾病,还是可细分为不同类别也尚不清楚。我们利用来自临床试验、基因本体论(GO)数据库以及基因表达数据的信息,根据GO数据库识别代表生物过程的无向依赖图(UDG)。对患病与未患病患者的UDG进行结构比较,使我们能够对发病机制导致的途径改变做出预测。