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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn / Kormeier, Benjamin

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan

4 Issues per year

Open Access
Online
ISSN
1613-4516
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Volume 3, Issue 2

Issues

Exact and Approximate Stochastic Simulations of the MAPK Pathway and Comparisons of Simulations’ Results

Vilda Purutçuoǧlu
  • Corresponding author
  • Department of Mathematics and Statistics, Lancaster Univer sity, Lancaster LA1 4YF, United Kingdom of Great Britain and Northern Ireland
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/ Ernst Wit
  • Department of Mathematics and Statistics, Lancaster Univer sity, Lancaster LA1 4YF, United Kingdom of Great Britain and Northern Ireland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-10-18 | DOI: https://doi.org/10.1515/jib-2006-38

Summary

The MAPK (mitogen-activated protein kinase) or its synonymous ERK (extracellular signal regulated kinase) pathway whose components are Ras, Raf, and MEK proteins with many biochemical links, is one of the major signalling systems involved in cellular growth control of eukaryotes including cell proliferation, transformation, differentiation, and apoptosis. In this study we describe the MAPK/ERK pathway via (quasi) biochemical reactions and then implement the pathway by a stochastic Markov process. A novelty of our approach is to use multiple parametrizations in order to deal with molecules for which localization in the cell is an intricate part of the dynamic process and to describe the protein using different binding sites and various phosphorylations. We simulate the system by exact and different approximate simulations, e.g. via the Poisson τ-leap, the Binomial τ-leap and the diffusion methods, in which we introduce a new updating plan for dependent columns of the diffusion matrix. Finally we compare the results of different algorithms by the current biological knowledge and find out new relations about this complex system.

About the article

Published Online: 2016-10-18

Published in Print: 2006-12-01


Citation Information: Journal of Integrative Bioinformatics, Volume 3, Issue 2, Pages 199–211, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2006-38.

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© 2006 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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