Optimal Constrained Stationary Intervention in Gene Regulatory Networks
Faryabi, B., Vahedi, G., Chamberland, J. F., Datta, A., and Dougherty, E. R., EURASIP Journal on Bioinformatics and Systems Biology, vol. 2008, Article ID 620767, 10 pages, doi: 10.1155/2008/620767, May, 2008
Abstract
A key objective of gene network modeling is to develop intervention strategies to alter regulatory dynamics in such a way as to reduce the likelihood of undesirable phenotypes. Optimal stationary intervention policies have been developed for gene regulation in the framework of probabilistic Boolean networks in a number of settings. To mitigate the possibility of detrimental side effects, for instance, in the treatment of cancer, it may be desirable to limit the expected number of treatments beneath some bound. This paper formulates a general constraint approach for optimal therapeutic intervention by suitably adapting the reward function and then applies this formulation to bound the expected number of treatments. A mutated mammalian cell cycle is considered as a case study.
