DocumentCode
2735765
Title
A Bayesian approach to expression network component analysis
Author
Sabatti, Chiara ; Rohlin, Lars
Author_Institution
Dept. of Stat. & Human Genetics, California Univ., Los Angeles, CA, USA
Volume
2
fYear
2004
fDate
1-5 Sept. 2004
Firstpage
2933
Lastpage
2936
Abstract
A semiblind deconvolution method of analysis for gene expression data was proposed recently in a series of articles appeared in PNAS. We illustrate here how similar goals can be achieved in a Bayesian framework and how necessary information on the presence of binding sites can be obtained with Vocabulon, an algorithm based on a stochastic dictionary model.
Keywords
belief networks; biology computing; genetics; molecular biophysics; stochastic processes; Bayesian approach; Vocabulon; binding sites; gene expression data; network component analysis; semiblind deconvolution method; stochastic dictionary model; Bayesian methods; Chemical analysis; Chemical engineering; Deconvolution; Gene expression; Genetics; Humans; Matrix decomposition; Proteins; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-8439-3
Type
conf
DOI
10.1109/IEMBS.2004.1403833
Filename
1403833
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