PMID- 17803373
OWN - NLM
STAT- MEDLINE
DCOM- 20080122
LR  - 20070906
IS  - 1066-5277 (Print)
IS  - 1066-5277 (Linking)
VI  - 14
IP  - 7
DP  - 2007 Sep
TI  - The chronic fatigue syndrome: a comparative pathway analysis.
PG  - 961-72
AB  - 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.
FAU - Emmert-Streib, Frank
AU  - Emmert-Streib F
AD  - Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA. 
      fes@stowers-institute.org
LA  - eng
PT  - Journal Article
PL  - United States
TA  - J Comput Biol
JT  - Journal of computational biology : a journal of computational molecular cell 
      biology
JID - 9433358
SB  - IM
MH  - *Algorithms
MH  - Clinical Trials as Topic
MH  - Databases, Genetic
MH  - *Fatigue Syndrome, Chronic/diagnosis/genetics/physiopathology
MH  - Gene Expression Profiling
MH  - Humans
MH  - Mathematics
EDAT- 2007/09/07 09:00
MHDA- 2008/01/23 09:00
CRDT- 2007/09/07 09:00
PHST- 2007/09/07 09:00 [pubmed]
PHST- 2008/01/23 09:00 [medline]
PHST- 2007/09/07 09:00 [entrez]
AID - 10.1089/cmb.2007.0041 [doi]
PST - ppublish
SO  - J Comput Biol. 2007 Sep;14(7):961-72. doi: 10.1089/cmb.2007.0041.