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Mathematical Modelling Plant Signalling Networks

Published online by Cambridge University Press:  10 July 2013

D. Muraro*
Affiliation:
Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham Sutton Bonington Campus, Loughborough LE12 5RD, UK Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, OX3 9DS, UK
H.M. Byrne
Affiliation:
Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham Sutton Bonington Campus, Loughborough LE12 5RD, UK Oxford Centre for Collaborative Applied Mathematics, Mathematical Institute, Oxford, OX1 3LB, UK School of Mathematical Sciences, University of Nottingham, University Park Nottingham NG7 2RD, UK
J.R. King
Affiliation:
Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham Sutton Bonington Campus, Loughborough LE12 5RD, UK School of Mathematical Sciences, University of Nottingham, University Park Nottingham NG7 2RD, UK
M.J. Bennett
Affiliation:
Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham Sutton Bonington Campus, Loughborough LE12 5RD, UK
*
Corresponding author. E-mail: daniele.muraro@ndm.ox.ac.uk
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Abstract

During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting.

Type
Research Article
Copyright
© EDP Sciences, 2013

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