BioNet

DOI: 10.18129/B9.bioc.BioNet  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see BioNet.

Routines for the functional analysis of biological networks

Bioconductor version: 3.17

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>

Installation

To install this package, start R (version "4.3") 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	1.60.0
In Bioconductor since	BioC 2.7 (R-2.12) (13 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_1.60.0.tar.gz
Windows Binary	BioNet_1.60.0.zip
macOS Binary (x86_64)	BioNet_1.60.0.tgz
macOS Binary (arm64)	BioNet_1.60.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/BioNet
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/BioNet
Bioc Package Browser	https://code.bioconductor.org/browse/BioNet/
Package Short Url	https://bioconductor.org/packages/BioNet/
Package Downloads Report	Download Stats