Robust intervention in probabilistic boolean networks

Ranadip Pal, Aniruddha Datta, Edward R. Dougherty

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

Abstract

One of the objectives of genetic regulatory network modeling is to design intervention approaches for affecting the time evolution of the gene activity profile of the network. The intervention strategies proposed in the context of Probabilistic Boolean Networks (PBNs) assume perfect knowledge of the transition probability matrix of the PBN. This assumption cannot be satisfied in practice due to estimation errors or mismatch between the PBN model and the actual genetic regulatory network. In this paper, we develop a robust intervention strategy that is obtained by minimizing the worstcase cost over the uncertainties in the entries of the transition probability matrix.

Original languageEnglish
Title of host publicationConference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
Pages29-33
Number of pages5
DOIs
StatePublished - Dec 1 2007
Event41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States
Duration: Nov 4 2007Nov 7 2007

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Conference

Conference41st Asilomar Conference on Signals, Systems and Computers, ACSSC
CountryUnited States
CityPacific Grove, CA
Period11/4/0711/7/07

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Pal, R., Datta, A., & Dougherty, E. R. (2007). Robust intervention in probabilistic boolean networks. In Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC (pp. 29-33). [4487158] (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2007.4487158