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