CellNOptR-package {CellNOptR} | R Documentation |
This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data collected upon perturbation of some of the nodes in the network.
Package: | CellNOptR |
Type: | Package |
Version: | 1.25.1 |
Date: | 2018-01-10 |
License: | GPLv3 |
LazyLoad: | yes |
T. Cokelaer, A. MacNamara, F. Eduati, S. Schrier, C. Terfve
Maintainer: A. Gabor<gabor.attila87@gmail.com>, until 2018-01-18: T. Cokelaer <cokelaer@ebi.ac.uk>
J. Saez-Rodriguez, L. G. Alexopoulos, J. Epperlein, R. Samaga, D. A. Lauffenburger, S. Klamt and P. K. Sorger. Discrete logic modeling as a means to link protein signaling networks with functional analysis of mammalian signal transduction, Molecular Systems Biology, 5:331, 2009.
# quick 1 time point optimisation of a Prior Knowledge Network to MIDAS data. data(CNOlistToy,package="CellNOptR") data(ToyModel,package="CellNOptR") pknmodel = ToyModel cnolist = CNOlist(CNOlistToy) model = preprocessing(cnolist, pknmodel) results = gaBinaryT1(cnolist, model, verbose=FALSE) plotFit(results) cutAndPlot(cnolist, model, list(results$bString)) # Same as above and HTML report CNORwrap(name="Toy", namesData=list(CNOlist="ToyData",model="ToyModel"), data=CNOlistToy, model=pknmodel)