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A framework for mapping,visualisation and automatic model creation of signal‐transduction networks
Authors:Gunnar Cedersund  Robert Palmér  Edda Klipp  Stefan Hohmann  Hiroaki Kitano  Marcus Krantz
Institution:1. Department of Cell and Molecular Biology, University of Gothenburg, , G?teborg, Sweden;2. Department of Clinical and Experimental Medicine, Diabetes and Integrative Systems Biology, Link?ping University, , Link?ping, Sweden;3. Freiburg Institute of Advanced Sciences, School of Life Sciences, , Freiburg, Germany;4. Theoretical Biophysics, Humboldt‐Universit?t zu Berlin, , Berlin, Germany;5. The Systems Biology Institute, , Tokyo, Japan;6. Sony Computer Science Laboratories, Inc., , Tokyo, Japan;7. Okinawa Institute of Science and Technology, , Okinawa, Japan
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.
Keywords:combinatorial complexity  mathematical modelling  network mapping  signal transduction  visualisation
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