Gene network inference via sparse structural equation modeling with genetic perturbations

Xiaodong Cai, Juan Andrés Bazerque, Georgios B. Giannakis

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

3 Scopus citations

Abstract

Structural equation models (SEMs) have been recently proposed to infer gene regulatory network using gene expression data and genetic perturbations. However, lack of efficient inference method for SEMs prevents practical use of SEMs in the inference of relatively large gene networks. In this paper, relying on the sparsity of gene networks, we develop an efficient SEM-based method for inferring gene networks using both gene expression and expression quantitative trait locus (eQTL) data. Simulated tests demonstrate that the novel method significantly outperform state-of-the-art methods in the field.

Original languageEnglish (US)
Title of host publicationProceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
PublisherIEEE Computer Society
Pages66-69
Number of pages4
ISBN (Print)9781467304900
DOIs
StatePublished - 2011
Event2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11 - San Antonio, TX, United States
Duration: Dec 4 2011Dec 6 2011

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
CountryUnited States
CitySan Antonio, TX
Period12/4/1112/6/11

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

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