alexa Assessing Numerical Resolution Methods Performance for
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

Assessing Numerical Resolution Methods Performance for Kinetic Models of Receptors and Channels

Merdan Sarmis1,2, Jean-Marie C Bouteiller1,3*, Nicolas Ambert1, Arnaud Legendre1,2, Serge Bischoff1, Olivier Haeberlé2 and Michel Baudry1,4*

1Rhenovia Pharma SA, Mulhouse, France

2Laboratoire MIPS EA2332, Université de Haute Alsace, Mulhouse, France

3Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA

4Western University of Health Sciences, Pomona, CA, USA

*Corresponding Author:
Michel Baudry
Western University of Health Sciences
Pomona, CA, USA
Tel: (+33) 389 321 180
Fax: (+33) 389 555 145
E-mail:[email protected]
Jean-Marie C Bouteiller
Rhenovia Pharma SA, 20C Rue de Chemnitz
F-68200 Mulhouse, France
Tel: +33-389 321 180
Fax: +33-389 555 145
E-mail: jeanmarie [email protected]

Received date: June 17, 2013; Accepted date: July 19, 2013; Published date: July 22, 2013

Citation:Sarmis M, Bouteiller JMC, Ambert N, Legendre A, Bischoff S, et al. (2013) Assessing Numerical Resolution Methods Performance for Kinetic Models of Receptors and Channels. J Comput Sci Syst Biol 6:150-164. doi:10.4172/jcsb.1000112

Copyright: © 2013 Sarmis M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

In systems biology, systems of kinetic reactions are generally used to model and simulate various biochemical pathways. These reactions are translated into ordinary differential equations, which are computationally resolved by numerical algorithms. Computation performance, defined by how fast the algorithm converges to a numerical solution of the system of ordinary differential equations, critically depends on the choice of the appropriate algorithm. In this paper, we compared several algorithms used to solve ordinary differential equations applied to several kinetic models that describe the dynamic behavior of receptors and ion channels found in chemical synapses of the Central Nervous System; we provide a simplified method to determine the performances of these ordinary differential equation solvers, in order to provide a benchmark for algorithm selection. This method will facilitate the choice of the most efficient algorithm for a given kinetic model with a minimum number of tests. Our results provide a tool for identifying optimal solvers for any biological bilinear kinetic models under various experimental conditions. This comparison also underscored the complexity of biological kinetic models and illustrates how their input dependency could interfere with performance. Despite these challenges, our simplified method helps to select the best solvers for any synaptic receptors kinetic models described, with a bilinear system with minimal a priori information on the solver structure and the model.

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