Reconstructing transcriptional regulatory networks by probabilistic network component analysis

Jinghua Gu, Jianhua Xuan, Xiao Wang, Ayesha N. Shajahan, Leena Hilakivi-Clarke, Robert Clarke

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

1 Scopus citations

Abstract

Despite encouraging progress made by integrating multiplatform data for regulatory network reconstruction, identification of transcriptional regulatory networks remains challenging due to imperfection in current biotechnology and complexity of biological systems. It is important to develop new computational approaches for reliable regulatory network reconstruction, especially those of robustness against noise in gene expression data and 'structural error' (i.e., false connections) in binding data. We propose a new method, namely probabilistic network component analysis (pNCA), to estimate the posterior binding matrix given observed gene expression and binding data. The elements in the binding matrix, instead of taking deterministic binary values, are modeled as unknown Bernoulli random variables that represent the probability of regulation. A novel two-stage Gibbs sampling framework is employed to iteratively estimate both hidden transcription factor activities and the posterior distribution of binding matrix. Numerical simulation on synthetic data has demonstrated improved performance of the proposed method over several existing methods for regulatory network identification. Notably, the robustness of pNCA against 'structural error' in initial binding data is fortified with high tolerance of false negative connections in addition to that of false positive connections. The proposed method has been applied to breast cancer cell line data to reconstruct biologically meaningful regulatory networks, revealing condition-specific regulatory rewiring and important cooperative regulation associated with estrogen signaling and action in breast cancer cells.

Original languageEnglish (US)
Title of host publication2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
Pages96-105
Number of pages10
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013 - Wshington, DC, United States
Duration: Sep 22 2013Sep 25 2013

Publication series

Name2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

Other

Other2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
CountryUnited States
CityWshington, DC
Period9/22/139/25/13

Keywords

  • Constrained optimization
  • Gene regulatory networks
  • Gibbs sampling
  • Multivariate linear regression
  • Network component analysis

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