To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("BioNet")

In most cases, you don't need to download the package archive at all.

BioNet

Routines for the functional analysis of biological networks

Bioconductor version: 2.13

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 and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("BioNet")

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 bum1.pdf
PDF bum2.pdf
PDF cytoscape.pdf
PDF prec_recall_large.pdf
PDF prec_recall_small.pdf
PDF Tutorial-3dplot.pdf
PDF   Reference Manual

Details

biocViews DataImport, DifferentialExpression, GeneExpression, GraphsAndNetworks, Microarray, NetworkAnalysis, NetworkEnrichment, Software
Version 1.23.2
In Bioconductor since BioC 2.7 (R-2.12)
License GPL (>= 2)
Depends R (>= 2.10.0), Biobase, graph, RBGL
Imports igraph, AnnotationDbi
Suggests rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML
System Requirements
URL http://bionet.bioapps.biozentrum.uni-wuerzburg.de/
Depends On Me
Imports Me HTSanalyzeR
Suggests Me

Package Archives

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

Package Source BioNet_1.23.2.tar.gz
Windows Binary BioNet_1.23.2.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) BioNet_1.23.2.tgz
Browse/checkout source (username/password: readonly)
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