Optimal Constrained Stationary Intervention in Gene Regulatory Networks

被引:34
作者
Faryabi, Babak [1 ]
Vahedi, Golnaz [1 ]
Chamberland, Jean-Francois [1 ]
Datta, Aniruddha [1 ]
Dougherty, Edward R. [1 ,2 ]
机构
[1] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
[2] Translat Genom Res Inst, Computat Biol Div, Phoenix, AZ 85004 USA
基金
美国国家科学基金会;
关键词
D O I
10.1155/2008/620767
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 (C) 2008 Babak Faryabi et al.
引用
收藏
页数:10
相关论文
共 26 条
[1]  
Altman E, 1999, STOCH MODEL SER
[2]  
BERTSEKAS DP, 2001, DYNAMIC PROGRAMMING
[3]   Adenovirus-mediated wild-type p53 tumor suppressor gene therapy induces apoptosis and suppresses growth of human pancreatic cancer [J].
Bouvet, M ;
Bold, RJ ;
Lee, J ;
Evans, DB ;
Abbruzzese, JL ;
Chiao, PJ ;
McConkey, DJ ;
Chandra, J ;
Chada, S ;
Fang, BL ;
Roth, JA .
ANNALS OF SURGICAL ONCOLOGY, 1998, 5 (08) :681-688
[4]  
Boyd S., 2004, CONVEX OPTIMIZATION, DOI DOI 10.1017/CBO9780511804441
[5]   Steady-state probabilities for attractors in probabilistic Boolean networks [J].
Brun, M ;
Dougherty, ER ;
Shmulevich, I .
SIGNAL PROCESSING, 2005, 85 (10) :1993-2013
[6]   External control in Markovian Genetic Regulatory Networks [J].
Datta, A ;
Choudhary, A ;
Bittner, ML ;
Dougherty, ER .
MACHINE LEARNING, 2003, 52 (1-2) :169-191
[7]  
Datta A., 2006, INTRO GENOMIC SIGNAL
[8]  
Derman C., 1970, FINITE STATE MARKOVI
[9]   WAF1, A POTENTIAL MEDIATOR OF P53 TUMOR SUPPRESSION [J].
ELDEIRY, WS ;
TOKINO, T ;
VELCULESCU, VE ;
LEVY, DB ;
PARSONS, R ;
TRENT, JM ;
LIN, D ;
MERCER, WE ;
KINZLER, KW ;
VOGELSTEIN, B .
CELL, 1993, 75 (04) :817-825
[10]   On approximate stochastic control in genetic regulatory networks [J].
Faryabi, B. ;
Datta, A. ;
Dougherty, E. R. .
IET SYSTEMS BIOLOGY, 2007, 1 (06) :361-368