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classify diseases and build associated gene networks using gene expression profiles

Bioconductor version: 3.0

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>

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biocViews Classification, DifferentialExpression, Microarray, Software
Version 1.6.3
In Bioconductor since BioC 2.12 (R-3.0)
License GPL (>= 2)
Depends R (>= 2.10.1), Biobase(>= 2.5.5), EBarrays, minet, methods
Imports e1071, graphics
Suggests leukemiasEset, RUnit, BiocGenerics
Enhances RColorBrewer, igraph, infotheo
Depends On Me
Imports Me
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