An iterated conditional mode solution for Bayesian factor modeling of transcriptional regulatory networks

Jia Meng, Jianqiu Zhang, Yidong Chen, Yufei Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
DOIs
StatePublished - Dec 1 2010
Event2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010 - Cold Spring Harbor, NY, United States
Duration: Nov 10 2010Nov 12 2010

Publication series

Name2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010

Other

Other2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
CountryUnited States
CityCold Spring Harbor, NY
Period11/10/1011/12/10

    Fingerprint

ASJC Scopus subject areas

  • Genetics
  • Signal Processing

Cite this

Meng, J., Zhang, J., Chen, Y., & Huang, Y. (2010). An iterated conditional mode solution for Bayesian factor modeling of transcriptional regulatory networks. In 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010 [5719679] (2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010). https://doi.org/10.1109/GENSIPS.2010.5719679