TY - GEN
T1 - An iterated conditional mode solution for Bayesian factor modeling of transcriptional regulatory networks
AU - Meng, Jia
AU - Zhang, Jianqiu
AU - Chen, Yidong
AU - Huang, Yufei
PY - 2010
Y1 - 2010
N2 - The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM) coupled with its ICM solution is proposed. BSCRFM models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF regulated genes and it admits prior knowledge from existing database regarding TF regulated target genes. An efficient ICM algorithm is developed and a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the ICM algorithm are evaluated on the simulated systems and results demonstrated the validity and effectiveness of the proposed approach. The proposed model is also applied to the breast cancer microarray data and a TF regulated network regarding ER status is obtained.
AB - The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM) coupled with its ICM solution is proposed. BSCRFM models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF regulated genes and it admits prior knowledge from existing database regarding TF regulated target genes. An efficient ICM algorithm is developed and a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the ICM algorithm are evaluated on the simulated systems and results demonstrated the validity and effectiveness of the proposed approach. The proposed model is also applied to the breast cancer microarray data and a TF regulated network regarding ER status is obtained.
UR - http://www.scopus.com/inward/record.url?scp=79952809349&partnerID=8YFLogxK
U2 - 10.1109/GENSIPS.2010.5719679
DO - 10.1109/GENSIPS.2010.5719679
M3 - Conference Proceeding
AN - SCOPUS:79952809349
SN - 9781612847924
T3 - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
BT - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
T2 - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
Y2 - 10 November 2010 through 12 November 2010
ER -
