A framework for mapping, visualisation and automatic model creation of signal-transduction networks.
Journal article, 2012
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.
Models
enzymology
Software
Databases
Molecular
genetics
Factual
methods
Saccharomyces cerevisiae
Systems Biology
growth & development
Protein Interaction Mapping
Metabolic Networks and Pathways
Empirical Research
Computer Simulation
Signal Transduction
physiology
Author
Carl Fredrik Tiger
University of Gothenburg
Falko Krause
Gunnar Cedersund
University of Gothenburg
Robert Palmér
Edda Klipp
Stefan Hohmann
University of Gothenburg
Hiroaki Kitano
Marcus Krantz
University of Gothenburg
Molecular Systems Biology
17444292 (eISSN)
Vol. 8 artikel nr 578-Subject Categories
Biochemistry and Molecular Biology
DOI
10.1038/msb.2012.12
PubMed
22531118