Comparison of robust strategies for the control of gene regulatory networks Conference Paper

abstract

• The presence of noise and the availability of a limited number of samples prevent the transition probabilities of a gene regulatory network from being accurately estimated. Thus, it is important to study the effect of modeling errors on the final outcome of an intervention strategy and to design robust intervention strategies. Two major approaches applied to the design of robust policies in general are the Mini-Max (worst case) approach and the Bayesian approach. In this paper we will compare the Minimax, Bayesian and Global robustness approach with respect to intervention in genetic regulatory networks. 2008 IEEE.

name of conference

• 2008 IEEE International Workshop on Genomic Signal Processing and Statistics

authors

• Datta, Aniruddha
• Dougherty, Edward

published proceedings

• 2008 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS

author list (cited authors)

• Pal, R., Datta, A., & Dougherty, E.

citation count

• 0

complete list of authors

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

publication date

• June 2008

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics  Journal

keywords

• Biotechnology
• Genetics
• Prevention

Digital Object Identifier (DOI)

• 10.1109/gensips.2008.4555671

International Standard Book Number (ISBN) 13

• 978-1-4244-2371-2

start page

• 55

end page

• +

URL

• http://dx.doi.org/10.1109/gensips.2008.4555671