Robust intervention in Probabilistic Boolean Networks Conference Paper

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. 2007 IEEE.

name of conference

• 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers

authors

• Datta, Aniruddha
• Dougherty, Edward

published proceedings

• CONFERENCE RECORD OF THE FORTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1-5

author list (cited authors)

• Pal, R., Datta, A., & Dougherty, E. R.

citation count

• 0

complete list of authors

• Pal, Ranadip||Datta, Aniruddha||Dougherty, Edward R

publication date

• November 2007

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Conference record / Asilomar Conference on Signals, Systems & Computers. Asilomar Conference on Signals, Systems & Computers  Journal

keywords

• Genetics
• Prevention

Digital Object Identifier (DOI)

• 10.1109/acssc.2007.4487158

International Standard Book Number (ISBN) 13

• 978-1-4244-2109-1

start page

• 29

end page

• +

URL

• http://dx.doi.org/10.1109/acssc.2007.4487158