Welcome to rxncon

The purpose of rxncon is to provide a framework to collect, visualise and model experimental data on cellular networks. In the rxncon framework, cellular signal transduction networks are described at the same granularity as empirical data. The key feature is strict separation of elemental reactions from contingencies, which define contextual constrains on these reactions, and this separation minimises the combinatorial complexity. The user defines the network as one reaction list and one contingency list. From these data mathematical and graphical representation can be generated. The network can be easily modified and extended, and both visualization and mathematical models can be generated automatically at any time.


web2py server start gui def math viz all


When using rxncon, please cite:

Tiger, C.-F., Krause, F., Cedersund, G., Palmér, R., Klipp. E., Hohmann, S., Kitano, H. & Krantz, M. (2012) A framework for mapping, visualisation and automatic model creation of signal transduction networks. Molecular Systems Biology 8, 578.

Related articles:

Magdalena Rother, Ulrike Münzner, Sebastian Thieme and Marcus Krantz (2013)
Information content and scalability in signal transduction network reconstruction formats. Molecular BioSystems, DOI: 10.1039/C3MB00005B

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