Intervention in general topology gene regulatory networks

Nidhal Bouaynaya, Mohammed Rasheed, Roman Shterenberg, Dan Schonfeld

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

3 Scopus citations

Abstract

We present an optimal intervention framework in general topology gene regulatory networks. In particular, we do not make any assumptions about the structure or the connectivity of the initial gene network. The proposed framework finds an optimal perturbation, which forces the network to converge towards a unique desired steady-state distribution. We cast the intervention as an optimization problem, and we show that it admits at most one optimal solution. The existence of the optimal solution depends on the initial network topology and the desired steady-state distribution. In the case where no optimal solution exists, we construct a sequence of suboptimal perturbations, which converge towards a limiting optimal solution. The general topology intervention framework is applied to the Human melanoma gene regulatory network.

Original languageEnglish (US)
Title of host publicationProceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
PublisherIEEE Computer Society
Pages222-225
Number of pages4
ISBN (Print)9781467304900
DOIs
StatePublished - 2011
Externally publishedYes
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
Country/TerritoryUnited States
CitySan Antonio, TX
Period12/4/1112/6/11

All Science Journal Classification (ASJC) codes

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

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