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

Jia Meng, Jianqiu Zhang, Yidong Chen, Yufei Huang

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

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 Iterated Conditional Modes (ICM) algorithm is developed, and a maximum a posterior (MAP) solution is calculated from multiple ICM results to avoid the local maximum problem, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can then be obtained. The proposed model's ICM algorithm and MAP solution 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 is obtained.

Original languageEnglish (US)
Title of host publicationProceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Pages335-340
Number of pages6
DOIs
StatePublished - Dec 1 2010
Event2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 - Hong Kong, China
Duration: Dec 18 2010Dec 21 2010

Publication series

NameProceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

Other

Other2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
CountryChina
CityHong Kong
Period12/18/1012/21/10

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Meng, J., Zhang, J., Chen, Y., & Huang, Y. (2010). An iterated conditional modes solution for sparse Bayesian factor modeling of transcriptional regulatory networks. In Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 (pp. 335-340). [5706587] (Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010). https://doi.org/10.1109/BIBM.2010.5706587