Package: CellNOptR 1.59.0

Attila Gabor

CellNOptR: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.

Authors:Thomas Cokelaer [aut], Federica Eduati [aut], Aidan MacNamara [aut], S Schrier [ctb], Camille Terfve [aut], Enio Gjerga [ctb], Attila Gabor [cre]

CellNOptR_1.59.0.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
CellNOptR/json (API)
NEWS

# Install 'CellNOptR' in R:
install.packages('CellNOptR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On BioConductor:CellNOptR-1.59.0(bioc 3.24)CellNOptR-1.58.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cellbasedassayscellbiologyproteomicspathwaysnetworktimecourseimmunooncology

6.66 score 6 packages 127 scripts 542 downloads 25 mentions 81 exports 54 dependencies

Last updated from:bd7ff69ddb. Checks:1 WARNING, 11 NOTE, 2 OK. Indexed: yes.

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Exports:buildBitStringcheckSignalsCNOdataCNOlistCNORboolCNORwrapcompatCNOlistcompressModelcomputeScoreT1computeScoreTNcrossInhibitedDatacrossvalidateBooleancutAndPlotcutAndPlotResultsT1cutAndPlotResultsTNcutCNOlistcutModelcutNONCcutSimListdefaultParametersexhaustiveexpandGatesfindNONCgaBinaryT1gaBinaryTNgetCuesgetFitgetInhibitorsgetSignalsgetStimuligetTimepointsgetVariancesgraph2sifilpBinaryT1ilpBinaryT2ilpBinaryTNindexFindermakeCNOlistmapBackmodel2igraphmodel2sifnormaliseCNOlistplotplotCNOlistplotCNOlist2plotCNOlistLargeplotCNOlistLargePDFplotCNOlistPDFplotFitplotModelplotOptimResultsplotOptimResultsPanplotOptimResultsPDFprep4simprep4SimpreprocessingrandomizerandomizeCNOlistreadBNDreadBNETreadErrorsreadMIDASreadSBMLQualreadSifreadSIFresidualErrorsetSignals<-sif2graphsimulateT1simulateTNsimulatorT0simulatorT1simulatorTNtoSBMLwriteDotwriteErrorswriteMIDASwriteNetworkwriteReportwriteScaffoldwriteSIF

Dependencies:base64encBHBiocGenericsbitopsbslibcachemclicpp11digestevaluatefarverfastmapfontawesomefsgenericsggplot2gluegraphgtablehighrhtmltoolsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimepkgconfigR6rappdirsRBGLRColorBrewerRCurlRgraphvizrlangrmarkdownS7sassscalesstringistringrtinytexvctrsviridisLitewithrxfunXMLyaml

Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data with CellNOptR

Camille Terfve, Thomas Cokelaer, Aidan MacNamara, Enio Gjerga, Attila Gabor, Panuwat Trairatphisan, Julio Saez-Rodriguez

Rendered fromCellNOptR-vignette.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2022-03-22
Started: 2022-03-16

Readme and manuals

Help Manual

Help pageTopics
R version of CellNOptR, boolean featuresCellNOptR-package CellNOptR
Build a SIF table from a logic rule written in a stringbuild_sif_table_from_rule
Check the CNOlist and model matchingcheckSignals
Get data from a CellNOpt data repositoryCNOdata cnodata
Class '"CNOlist"'CNOlist CNOlist-class compatCNOlist,CNOlist-method getCues,CNOlist-method getInhibitors,CNOlist-method getSignals,CNOlist-method getStimuli,CNOlist-method getTimepoints,CNOlist-method getVariances,CNOlist-method length,CNOlist-method plot,CNOlist,CNOlist-method randomize,CNOlist-method readErrors,CNOlist-method setSignals<-,CNOlist-method writeErrors,CNOlist-method
List of CNOlist-class methodsCNOlist-methods compatCNOlist compatCNOlist,CNOlist getCues getCues,CNOlist getInhibitors getInhibitors,CNOlist getSignals getSignals,CNOlist getStimuli getStimuli,CNOlist getTimepoints getTimepoints,CNOlist getVariances getVariances,CNOlist getVariances,CNOlist,CNOlist-method length length,CNOlist length,CNOlist,ANY-method plot,CNOlist,CNOlist,CNOlist-method randomize randomize,CNOlist randomize,CNOlist,CNOlist-method readErrors readErrors,CNOlist setSignals<- setSignals<-,CNOlist setSignals<-,CNOlist,CNOlist-method writeErrors writeErrors,CNOlist
Data used for the DREAM3 challengeCNOlistDREAM
Toy dataCNOlistToy
Toy data with 2 time pointsCNOlistToy2
Simple Boolean analysis standaloneCNORbool
CNOR analysis wrapperCNORwrap
Compress a modelcompressModel
Compute the score of a model/data set using a bitString to cut the model.computeScoreT1
Compute the score at TN of a model/data set using a bitString to cut the model.computeScoreTN
Defining the set of binary variables for the ILP implementation of CellNOptR.create_binaries
Creating and running the ILP problem.createAndRunILP
Reading the optimal solutions as bitstrings.createILPBitstringAll
If an inhibitor is also a measured species, replace the data with NA (when inhibited)crossInhibitedData
k-fold crossvalidation for Boolean model.crossvalidateBoolean
Interface to cutAndPlotResults functions.cutAndPlot
Plot the results of an optimisation at t1cutAndPlotResultsT1
Plot the results of an optimisation at tNcutAndPlotResultsTN
Cut a CNOlist structure according to a modelcutCNOlist
Cut a model structure according to a bitstringcutModel
Cuts the non-observable/non-controllable species from the modelcutNONC
Cut a simList structure according to a bitstringcutSimList
Create a list of default parametersdefaultParameters
Exhaustive search over the optimisation of a PKN model on MIDAS data.exhaustive
Expand the gates of a modelexpandGates
Find the indexes of the non-observable and non controllable speciesfindNONC
Genetic algorithm used to optimise a modelgaBinaryT1
Genetic algorithm for time point NgaBinaryTN
Compute the score of a modelgetFit
Convert graph to SIFgraph2sif
ILP method used to optimise a modelilpBinaryT1
ILP method used to optimise a modelilpBinaryT2
ILP method used to optimise a modelilpBinaryTN
Finds the indices, in the model fields, of the species that are measured/inhibited/stimulatedindexFinder
List of CellNOptR internal functions.internals
Solving the ILP problem with CPLEX.invokeCPLEX
Model used for the DREAM3 challengeDreamModel
Make a CNOlist structuremakeCNOlist
Map an optimised model back onto the PKN model.mapBack
Convert a model object to a igraph objectmodel2igraph
Convert a model object in sif formatmodel2sif
Normalisation for boolean modelling.normaliseCNOlist
pknmodelpknmodel
plot a '"CNOlist"' object - methodsplot,CNOlist,ANY-method plot.CNOlist
Plot the data in a CNOlistplotCNOlist
Another version of plotCNOlist that allows to plot 2 cnolist in the same layout to compare them. This function uses ggplot2 library. It is recommended for small data sets (about 15 species).plotCNOlist2
Plot the data in a CNOlist, for lists with many conditions.plotCNOlistLarge
Plots a CNOlist into a pdf file, for lists with many conditions.plotCNOlistLargePDF
Plots a CNOlist into a pdf file.plotCNOlistPDF
Plot the evolution of an optimisationplotFit
Plot a modelplotModel
Plot the data and simulated valuesplotOptimResults
Plots the data and simulated values from any CellNOptR formalismplotOptimResultsPan
Plot the data and simulated values in a pdf fileplotOptimResultsPDF
Prepare a model for simulationprep4Sim prep4sim
Performs the pre-processing stepspreprocessing
add noise to the data contained in a CNOlist.randomizeCNOlist
Read network from BND filereadBND
Read network from BNET filereadBNET
Reads in a CSV MIDAS filereadMIDAS readMidas
Read a SBMLQual document and returns a SIF object (as returned by readSIGreadSBMLQual
Read a SIF file and create a model objectreadSIF readSif
Compute the residual error for a datasetresidualError
Convert sif to graphsif2graph
Cut and simulation of a boolean model at t1simulateTN
Simulation of a boolean modelsimulatorT0
Simulation of a boolean modelsimulatorT1
Simulation of a boolean model at any time points dependent on a previous one.simulatorTN
Export the network to SBML-qual formattoSBML
Toy modelToyModel
Toy modelToyModel2
Writing the set of boundaries for each integer variable for the ILP implementation of CellNOptR.write_bounds
Writing the set of constraints for the ILP implementation of CellNOptR.write_constraints
Write a model, and attached features, to a dot filewriteDot
Writing the ILP problem.writeFile
Write a CNOlist structure into a MIDAS filewriteMIDAS
Write a previous knowledge network model to a sif file (with attribute files), as well as a dot filewriteNetwork
Writing the objective function for the ILP implementation of CellNOptR.writeObjectiveFunction
Write a report of a CellNOptR analysiswriteReport
Writes the scaffold network to a sif file (with attributes) and to a dot filewriteScaffold
Convert a model into a SIF format and save the result in a file.writeSIF writeSif