BioNet

DOI: 10.18129/B9.bioc.BioNet  

This is the development version of BioNet; for the stable release version, see BioNet.

Routines for the functional analysis of biological networks

Bioconductor version: Development (3.19)

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 "4.4") and enter:

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("BioNet")

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

Documentation

PDF		Reference Manual

Details

biocViews	DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software
Version	1.63.0
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	gatom, SMITE
Suggests Me	SANTA
Links To Me
Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
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