BioNet
Routines for the functional analysis of biological networks
Bioconductor version: Release (3.20)
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("BioNet")):
Installation
To install this package, start R (version "4.4") 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")| BioNet Tutorial | R Script | |
| Reference Manual |
Details
| biocViews | DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software |
| Version | 1.66.0 |
| In Bioconductor since | BioC 2.7 (R-2.12) (14 years) |
| License | GPL (>= 2) |
| Depends | R (>= 2.10.0), graph, RBGL |
| Imports | igraph (>= 1.0.1), AnnotationDbi, Biobase |
| System Requirements | |
| URL | http://bionet.bioapps.biozentrum.uni-wuerzburg.de/ |
See More
| Suggests | rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | gatom, SMITE |
| Suggests Me | SANTA, mwcsr |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | BioNet_1.66.0.tar.gz |
| Windows Binary (x86_64) | BioNet_1.66.0.zip |
| macOS Binary (x86_64) | BioNet_1.66.0.tgz |
| macOS Binary (arm64) | BioNet_1.66.0.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 |