DocumentCode :
3542535
Title :
Pathway analysis in the context of Bayesian networks - mathematical modeling of master and canalizing genes
Author :
Zhao, Chen ; Ivanov, Ivan ; Bittner, Michael L. ; Dougherty, Edward R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
fYear :
2011
fDate :
4-6 Dec. 2011
Firstpage :
64
Lastpage :
65
Abstract :
We utilize a tree-structured Bayesian network to characterize and detect master and canalizing genes via the coefficient of determination (CoD). Master genes possess strong regulation over groups of genes, whereas canalizing genes take over the regulation of large cohorts under certain cell conditions. While related, the two concepts are not the same and the analytic measures we employ reveal that difference. We also consider hypothesis testing for successful drug intervention in the framework of the Bayesian model.
Keywords :
belief networks; drugs; genetics; genomics; physiological models; signal processing; Bayesian networks; canalizing genes; coefficient of determination; drug intervention; hypothesis testing; master genes; pathway analysis; signal-processing model; Bayesian methods; Bioinformatics; Computational modeling; Drugs; Histograms; Irrigation; USA Councils;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on
Conference_Location :
San Antonio, TX
ISSN :
2150-3001
Print_ISBN :
978-1-4673-0491-7
Electronic_ISBN :
2150-3001
Type :
conf
DOI :
10.1109/GENSiPS.2011.6169444
Filename :
6169444
Link To Document :
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