Chronic Fatigue Syndrome Research Today is a free monthly online journal that collates and summarizes the latest research about Chronic Fatigue Syndrome, including details on myalgic encephalomyelitis (me), diagnosis, gradual and sudden onset.

Interpreter of maladies: redescription mining applied to biomedical data analysis.

Waltman P, Pearlman A, Mishra B

New York University, Courant Institute of Mathematical Sciences, 715 Broadway, New York, NY 10003, USA. mishra@nyu.edu

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Published 13 April 2006 in Pharmacogenomics, 7(3): 503-9.
Full-text of this article is available online (may require subscription).

© 2005-2008 Chronic Fatigue Syndrome Research Today. All Rights Reserved.