Welcome to rxncon

rxncon is a framework to build, visualise and model cellular signal transduction networks. The rxncon language enables the description of these networks. The rxncon software tool interprets the rxncon language and automates export into a range of graphical and mathematical formats.

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. Elemental reactions are generic reactions, and the contingencies define contextual constraints these reactions. 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 modified and extended iteratively, and both visualisation and mathematical models can be generated automatically at any time.


We are currently finalising a major overhaul of the interpretation engine and the export features.

web2py server start gui def math viz all


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.

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

Max Flöttmann, Falko Krause, Edda Klipp and Marcus Krantz (2013)
Reaction-contingency based bipartite Boolean modelling. BMC Systems Biology 2013, 7:58, DOI:10.1186/1752-0509-7-58

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