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A framework for mapping, visualisation and automatic model creation of signal-transduction networks
Humboldt University.
Humboldt University.
Linköping University, Department of Clinical and Experimental Medicine, Cell Biology. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences.
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2012 (English)In: Molecular Systems Biology, ISSN 1744-4292, Vol. 8, no 578Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Nature Publishing Group / European Molecular Biology Organization , 2012. Vol. 8, no 578
Keyword [en]
combinatorial complexity, mathematical modelling, network mapping, signal transduction, visualisation
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-77734DOI: 10.1038/msb.2012.12ISI: 000303451400001OAI: diva2:529036

Funding Agencies|JSPS||SSF (Japan)||Lions||Swedish Research Council||German Ministry for Education and Research (BMBF)||European Commission|20114235995043310514169|MULTIDISCIPLINARY BIO Sweden-Japan initiative (Sweden: Foundation for Strategic Research SSF and Vinnova, Japan: Japan Science and Technology Agency JST)||Swedish Research Council|2007-4905|

Available from: 2012-05-29 Created: 2012-05-28 Last updated: 2014-10-30

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