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
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;
Conference_Titel :
Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4673-0491-7
Electronic_ISBN :
2150-3001
DOI :
10.1109/GENSiPS.2011.6169444