tailieunhanh - Báo cáo hóa học: " Research Article Optimal Constrained Stationary Intervention in Gene Regulatory Networks"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Optimal Constrained Stationary Intervention in Gene Regulatory Networks | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2008 Article ID 620767 10 pages doi 2008 620767 Research Article Optimal Constrained Stationary Intervention in Gene Regulatory Networks Babak Faryabi 1 Golnaz Vahedi 1 Jean-Francois Chamberland 1 Aniruddha Datta 1 and Edward R. Dougherty1 2 1 Department of Electrical and Computer Engineering Texas A M University College Station TX 77843 USA 2 Computational Biology Division Translational Genomics Research Institute Phoenix AZ 85004 USA Correspondence should be addressed to Edward R. Dougherty edward@ Received 11 January 2008 Accepted 9 April 2008 Recommended by Yufei Huang 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. Copyright 2008 Babak Faryabi et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction One objective of genetic regulatory modeling is to design intervention strategies that affect the evolution of the gene activity profile of the network. Such strategies can be useful in identifying potential drug targets and treatment methods to alter network .