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Classify diseases and build associated gene networks using gene expression profiles

Bioconductor version: Release (3.19)

Comprehensive package to automatically train and validate a multi-class SVM classifier based on gene expression data. Provides transparent selection of gene markers, their coexpression networks, and an interface to query the classifier.

Author: Sara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain.

Maintainer: Sara Aibar <saibar at>

Citation (from within R, enter citation("geNetClassifier")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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


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

geNetClassifier-vignette PDF R Script
Reference Manual PDF


biocViews Classification, DifferentialExpression, Microarray, Software
Version 1.44.0
In Bioconductor since BioC 2.12 (R-3.0) (11.5 years)
License GPL (>= 2)
Depends R (>= 2.10.1), Biobase(>= 2.5.5), EBarrays, minet, methods
Imports e1071, graphics, grDevices
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Suggests leukemiasEset, RUnit, BiocGenerics
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Follow Installation instructions to use this package in your R session.

Source Package geNetClassifier_1.44.0.tar.gz
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macOS Binary (x86_64) geNetClassifier_1.44.0.tgz
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