Comparison of robust strategies for the control of gene regulatory networks

Ranadip Pal, Aniruddha Datta, Edward Dougherty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationGENSIPS'08 - 6th IEEE International Workshop on Genomic Signal Processing and Statistics
DOIs
StatePublished - 2008
Event6th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'08 - Phoenix, AZ, United States
Duration: Jun 8 2008Jun 10 2008

Publication series

NameGENSIPS'08 - 6th IEEE International Workshop on Genomic Signal Processing and Statistics

Conference

Conference6th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'08
Country/TerritoryUnited States
CityPhoenix, AZ
Period06/8/0806/10/08

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