Estimation of kinetic rates of MAP kinase activation from experimental data

Tian, T. (2009) Estimation of kinetic rates of MAP kinase activation from experimental data. In: Zhang, J., Li, G. and Yang, J.Y. (eds.) IJCBS 2009: 2009 International Joint Conference on Bioinformatics, Systems Biology and Intellgent Computing: Proceedings, 3-5 August 2009, Shanghai, China. IEEE Computer Society: Los Alamitos, USA, pp. 457-462. ISBN 9780769537399

Abstract

Mathematical model is an important tool in systems biology to study the dynamics of biological systems inside the cell. One of the significant challenges in systems biology is the lack of kinetic rates that should be measured in experiments or estimated from experimental data. This work addresses this issue by using a genetic algorithm to estimate reaction rates related to the phosphorylation and dephosphorylation of MAP kinase (ERK) in the mitogen-activated protein (MAP) kinase pathway from biological measurements. In addition, we discuss the robustness of the mathematical model with regards to the variation of kinetic rates together with external noise due to environmental fluctuations. This has been proposed as an additional criterion to choose the estimate from the candidate parameter sets that are obtained from different implementations of the genetic algorithm.

• Item Type: Book Sections
• Additional Information: ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
• Status: Published
• Glasgow Author(s) Enlighten ID: Tian, Dr Tianhai
• Authors: Tian, T.
• Subjects: Q Science > QA Mathematics; Q Science > QH Natural history > QH301 Biology
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Mathematics
• Publisher: IEEE Computer Society
• ISBN: 9780769537399
• Copyright Holders: Copyright © 2009 IEEE Computer Society
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.