CellNOpt (from CellNetOptimizer; a.k.a. CNO) is a software used for creating logic-based models of signal transduction networks using different logic formalisms (Boolean, Fuzzy, or differential equations). CellNOpt uses information on signaling pathways encoded as a Prior Knowledge Network, and trains it against high-throughput biochemical data to create cell-specific models. CellNOpt is freely available under GPL license in R and Matlab languages. It can be also accessed through a python wrapper, and a Cytoscape plugin called CytoCopter provides a graphical user interface. CellNOpt is mainly developed at the Saez-Rodriguez group at the European Bioinformatics Institute (EBI). The project started at the groups of Peter Sorger (Harvard Medical School) and Doug Lauffenburger (M.I.T.). There is a group of CellNOpt developers at different locations.
Keywords for this software
References in zbMATH (referenced in 1 article )
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- Videla, Santiago; Guziolowski, Carito; Eduati, Federica; Thiele, Sven; Gebser, Martin; Nicolas, Jacques; Saez-Rodriguez, Julio; Schaub, Torsten; Siegel, Anne: Learning Boolean logic models of signaling networks with ASP (2015)
Further publications can be found at: http://www.cellnopt.org/literature.html