Categories: automation, graph analysis, integrated analysis, logic modelling, network manipulation, simulation, systems biology

<http://www.cellnopt.org> Based on prior knowledge network and perturbation data, CellNOpt can derive functional information about the network using logic modeling. **CytoCopteR** is a friendly way to use CellNOpt taking advantage of the network visualization and analysis of Cytoscape and without requiring knowledge of programming languages. Version 2.0 relies on the Cyrface and CellNOptR R package. However, Version 3.x is a pure independent Java implementation. [http://msb.embopress.org/content/5/1/331.export Saez‐Rodriguez, J., Alexopoulos, L. G., Epperlein, J., Samaga, R., Lauffenburger, D. A., Klamt, S., Sorger, P. K. (2009). Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction. Molecular Systems Biology, 5, 1. doi:10.1038/msb.2009.87] [http://www.biomedcentral.com/content/pdf/1752-0509-6-133.pdf Terfve, C., Cokelaer, T., Henriques, D., MacNamara, A., Gonçalves, E., Morris, M. K., et al. (2012). CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms. BMC Systems Biology, 6, 133. doi:10.1186/1752-0509-6-133]

Authors:

• Mahdi Saber (JRC-COMBINE, RWTH-Aachen )
• Emanuel Goncalves (EMBL-European Bioinformatics Institute)
• Martijn van Iersel (EMBL-European Bioinformatics Institute)
• Francesco Ceccarelli (JRC-COMBINE, RWTH-Aachen )
• Attila Gabor (JRC-COMBINE, RWTH-Aachen)
• Julio Saez-Rodriguez (EMBL-European Bioinformatics Institute)