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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 (3.18)

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 "4.3") 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

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

browseVignettes("BioNet")
BioNet Tutorial PDF R Script
Reference Manual PDF

Details

biocViews DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software
Version 1.61.0
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
Linking To
Suggests rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML
System Requirements
Enhances
URL http://bionet.bioapps.biozentrum.uni-wuerzburg.de/
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Imports Me SMITE
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Build Report  

Package Archives

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

Source Package BioNet_1.61.0.tar.gz
Windows Binary BioNet_1.61.0.zip (64-bit only)
macOS Binary (x86_64) BioNet_1.61.0.tgz
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
Bioc Package Browser https://code.bioconductor.org/browse/BioNet/
Package Short Url https://bioconductor.org/packages/BioNet/
Package Downloads Report Download Stats