SPSens: A software package for stochastic parameter sensitivity analysis of biochemical reaction networks

Bioinformatics

Volumn 29, Issue 1, 2013, Pages 140-142

  Sheppard, Patrick W ^a   Rathinam, Muruhan ^b   Khammash, Mustafa ^a  

^a ETH ZURICH   (Switzerland)

^b UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOCHEMISTRY; COMPUTER PROGRAM; MONTE CARLO METHOD; STATISTICS;

ALGORITHMS; BIOCHEMICAL PROCESSES; MONTE CARLO METHOD; SOFTWARE; STOCHASTIC PROCESSES;

EID: 84871780271     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts642     Document Type: Article

References (8)

1. Anderson, D. (2012) An efficient finite difference method for parameter sensitivities of continuous time markov chains. SIAM J. Numer. Anal., 50, 2237-2258.
2. Gillespie, D. (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comput. Phys., 22, 403-434.
3. Gillespie, D. (1977) Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem., 81, 2340-2361.
4. Komorowski, M. et al. (2012) Stochsens-MATLAB package for sensitivity analysis of stochastic chemical systems. Bioinformatics, 28, 731-733.
5. L'Ecuyer, P. et al. (2002) An object-oriented random-number package with many long streams and substreams. Oper. Res., 50, 1073-1075.
6. Plyasunov, S. and Arkin, A. (2007) Efficient stochastic sensitivity analysis of discrete event systems. J. Comput. Phys., 221, 724-738.
7. Rathinam, M. et al. (2010) Efficient computation of parameter sensitivities of discrete stochastic chemical reaction networks. J. Chem. Phys., 132, 034103.
8. Sheppard, P. et al. (2012) A pathwise derivative approach to the computation of parameter sensitivities in discrete stochastic chemical systems. J. Chem. Phys., 136, 34115.