A framework for mapping, visualisation and automatic model creation of signal‐transduction networks

Molecular Systems Biology

Carl-Fredrik Tiger¹  Falko Krause³  Gunnar Cedersund¹  Robert Palmér²  Edda Klipp³  Stefan Hohmann¹  Hiroaki Kitano² 

[1] Department of Cell and Molecular Biology, University of Gothenburg, Göteborg, Sweden;Department of Clinical and Experimental Medicine, Diabetes and Integrative Systems Biology, Linköping University, Linköping, Sweden;Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany

关键词: combinatorial complexity;    mathematical modelling;    network mapping;    signal transduction;    visualisation;   

DOI  :  10.1038/msb.2012.12

来源: Wiley

【 摘 要 】

Abstract

Intracellular signalling systems are highly complex. This complexity makes handling, analysis and visualisation of available knowledge a major challenge in current signalling research. Here, we present a novel framework for mapping signal-transduction networks that avoids the combinatorial explosion by breaking down the network in reaction and contingency information. It provides two new visualisation methods and automatic export to mathematical models. We use this framework to compile the presently most comprehensive map of the yeast MAP kinase network. Our method improves previous strategies by combining (I) more concise mapping adapted to empirical data, (II) individual referencing for each piece of information, (III) visualisation without simplifications or added uncertainty, (IV) automatic visualisation in multiple formats, (V) automatic export to mathematical models and (VI) compatibility with established formats. The framework is supported by an open source software tool that facilitates integration of the three levels of network analysis: definition, visualisation and mathematical modelling. The framework is species independent and we expect that it will have wider impact in signalling research on any system.

Synopsis

An intuitive formalism for reconstructing cellular networks from empirical data is presented, and used to build a comprehensive yeast MAP kinase network. The accompanying rxncon software tool can convert networks to a range of standard graphical formats and mathematical models.

• Network mapping at the granularity of empirical data that largely avoids combinatorial complexity
• Automatic visualisation and model generation with the rxncon open source software tool
• Visualisation in a range of formats, including all three SBGN formats, as well as contingency matrix or regulatory graph
• Comprehensive and completely references map of the yeast MAP kinase network in the rxncon format

【 授权许可】

CC BY-NC-SA   
Copyright © 2012 EMBO and Macmillan Publishers Limited

Creative Commons Attribution License, which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation without specific permission.