CellNOptR

This package is for version 3.18 of Bioconductor; for the stable, up-to-date release version, see CellNOptR.

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

Bioconductor version: 3.18

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.

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

Maintainer: Attila Gabor <attila.gabor at uni-heidelberg.de>

Citation (from within R, enter citation("CellNOptR")):

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
BiocManager::install("CellNOptR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("CellNOptR")

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

Reference Manual PDF

NEWS Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews CellBasedAssays, CellBiology, ImmunoOncology, Network, Pathways, Proteomics, Software, TimeCourse

Version 1.48.0

In Bioconductor since BioC 2.9 (R-2.14) (12.5 years)

License GPL-3

Depends R (>= 4.0.0), RBGL, graph, methods, RCurl, Rgraphviz, XML, ggplot2, rmarkdown

Imports igraph, stringi, stringr

System Requirements Graphviz version>= 2.2

URL

Suggests data.table, dplyr, tidyr, readr, knitr, RUnit, BiocGenerics

Linking To

Enhances doParallel, foreach

Depends On Me CNORdt, CNORfeeder, CNORfuzzy, CNORode

Imports Me bnem

Suggests Me MEIGOR

Links To Me

Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package CellNOptR_1.48.0.tar.gz

Windows Binary CellNOptR_1.48.0.zip

macOS Binary (x86_64) CellNOptR_1.48.0.tgz

macOS Binary (arm64) CellNOptR_1.48.0.tgz

Source Repository git clone https://git.bioconductor.org/packages/CellNOptR

Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CellNOptR

Bioc Package Browser https://code.bioconductor.org/browse/CellNOptR/

Package Short Url https://bioconductor.org/packages/CellNOptR/

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