DocumentCode
1900495
Title
A Bayesian Approach for Uncovering Gene Network Motifs
Author
Yin, Yufang ; Huang, Yufei ; Shanmugam, Viji ; Brun, Marcel ; Hua, Jianping ; Dougherty, Edward R.
Author_Institution
Univ. of Texas at San Antonio, San Antonio
fYear
2007
fDate
10-12 June 2007
Firstpage
1
Lastpage
2
Abstract
Gene network motifs are the recurring regulatory structural patterns in gene networks. For uncovering gene network motifs, we investigate a novel Bayesian approach based on the popular turbo algorithm. The motivation for using turbo algorithm is based on the subtle similarity between the network motifs detection and turbo decoding in communications. The proposed method has been tested on two types of human cancer microarray data.
Keywords
Bayes methods; cancer; genetic engineering; genetics; Bayesian approach; gene network; human cancer microarray data; regulatory structural patterns; turbo algorithm; turbo decoding; Bayesian methods; Bioinformatics; Cancer detection; Decoding; Genomics; Humans; Neoplasms; Robustness; Testing; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Genomic Signal Processing and Statistics, 2007. GENSIPS 2007. IEEE International Workshop on
Conference_Location
Tuusula
Print_ISBN
978-1-4244-0998-3
Electronic_ISBN
978-1-4244-0999-0
Type
conf
DOI
10.1109/GENSIPS.2007.4365838
Filename
4365838
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