TY - GEN
T1 - Production-passage-time approximation
T2 - 11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007
AU - Kuwahara, Hiroyuki
AU - Myers, Chris
PY - 2007
Y1 - 2007
N2 - Given the substantial computational requirements of stochastic simulation, approximation is essential for efficient analysis of any realistic biochemical system. This paper introduces a new approximation method to reduce the computational cost of stochastic simulations of an enzymatic reaction scheme which in biochemical systems often includes rapidly changing fast reactions with enzyme and enzyme-substrate complex molecules present in very small counts. Our new method removes the substrate dissociation reaction by approximating the passage time of the formation of each enzyme-substrate complex molecule which is destined to a production reaction. This approach skips the firings of unimportant yet expensive reaction events, resulting in a substantial acceleration in the stochastic simulations of enzymatic reactions. Additionally, since all the parameters used in our new approach can be derived by the Michaelis-Menten parameters which can actually be measured from experimental data, applications of this approximation can be practical even without having full knowledge of the underlying enzymatic reaction. Furthermore, since our approach does not require a customized simulation procedure for enzymatic reactions, it allows biochemical systems that include such reactions to still take advantage of standard stochastic simulation tools. Here, we apply this new method to various enzymatic reaction systems, resulting in a speedup of orders of magnitude in temporal behavior analysis without any significant loss in accuracy.
AB - Given the substantial computational requirements of stochastic simulation, approximation is essential for efficient analysis of any realistic biochemical system. This paper introduces a new approximation method to reduce the computational cost of stochastic simulations of an enzymatic reaction scheme which in biochemical systems often includes rapidly changing fast reactions with enzyme and enzyme-substrate complex molecules present in very small counts. Our new method removes the substrate dissociation reaction by approximating the passage time of the formation of each enzyme-substrate complex molecule which is destined to a production reaction. This approach skips the firings of unimportant yet expensive reaction events, resulting in a substantial acceleration in the stochastic simulations of enzymatic reactions. Additionally, since all the parameters used in our new approach can be derived by the Michaelis-Menten parameters which can actually be measured from experimental data, applications of this approximation can be practical even without having full knowledge of the underlying enzymatic reaction. Furthermore, since our approach does not require a customized simulation procedure for enzymatic reactions, it allows biochemical systems that include such reactions to still take advantage of standard stochastic simulation tools. Here, we apply this new method to various enzymatic reaction systems, resulting in a speedup of orders of magnitude in temporal behavior analysis without any significant loss in accuracy.
UR - http://www.scopus.com/inward/record.url?scp=34547416021&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-71681-5_12
DO - 10.1007/978-3-540-71681-5_12
M3 - Conference contribution
AN - SCOPUS:34547416021
SN - 3540716807
SN - 9783540716808
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 166
EP - 180
BT - Research in Computational Molecular Biology - 11th Annual International Conference, RECOMB 2007, Proceedings
PB - Springer Verlag
Y2 - 21 April 2007 through 25 April 2007
ER -