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

Blumer KJ

Carl‐Fredrik Tiger

Chylek LA

Danos V

Davenport KD

Dowell SJ

Edda Klipp

Falko Krause

Green R

Gunnar Cedersund

Hiroaki Kitano

Inouye C

Ketela T

Madden K

Marcus Krantz

Mattison CP

Ostrander DB

Robert Palmér

Stefan Hohmann

Thorner J

Watanabe M

Zheng Y

Molecular Systems Biology

English

PubMed

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.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|</p

Tiger, Carl-Fredrik

Krause, Falko

Cedersund, Gunnar

Palmér, Robert

Klipp, Edda

Hohmann, Stefan

Kitano, Hiroaki

Krantz, Marcus

Academic Archive On-line (Linköping University, Sweden)

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

Crossref

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

Publikationer från Linköpings universitet

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

Tiger, Carl Fredrik

Palm\ue9r, Robert

Chalmers Research

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

Digitala Vetenskapliga Arkivet - Academic Archive On-line

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http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3361003

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

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Academic Archive On-line (Linköping University, Sweden)

Crossref

Publikationer från Linköpings universitet

Chalmers Research

Digitala Vetenskapliga Arkivet - Academic Archive On-line