BioNet

DOI: 10.18129/B9.bioc.BioNet    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see BioNet.

Routines for the functional analysis of biological networks

Bioconductor version: 3.15

This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.

Author: Marcus Dittrich and Daniela Beisser

Maintainer: Marcus Dittrich <marcus.dittrich at biozentrum.uni-wuerzburg.de>

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

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("BioNet")

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("BioNet")

 

PDF R Script BioNet Tutorial
PDF   Reference Manual

Details

biocViews DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software
Version 1.56.0
In Bioconductor since BioC 2.7 (R-2.12) (12 years)
License GPL (>= 2)
Depends R (>= 2.10.0), graph, RBGL
Imports igraph (>= 1.0.1), AnnotationDbi, Biobase
LinkingTo
Suggests rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML
SystemRequirements
Enhances
URL http://bionet.bioapps.biozentrum.uni-wuerzburg.de/
Depends On Me
Imports Me SMITE
Suggests Me SANTA
Links To Me
Build Report  

Package Archives

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

Source Package BioNet_1.56.0.tar.gz
Windows Binary BioNet_1.56.0.zip
macOS Binary (x86_64) BioNet_1.56.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/BioNet
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/BioNet
Package Short Url https://bioconductor.org/packages/BioNet/
Package Downloads Report Download Stats

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