The chronic fatigue syndrome: a comparative pathway analysis.
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.
Emmert-Streib
Frank
F
Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA. fes@stowers-institute.org
D000465:Algorithms; D002986:Clinical Trials as Topic; D030541:Databases, Genetic; D015673:Fatigue Syndrome, Chronic / Q000175:diagnosis / Q000235:genetics / Q000503:physiopathology; D020869:Gene Expression Profiling; D006801:Humans; D008433:Mathematics