LIBGS: A MATLAB software package for gene selection

Authors:
Yi Zhang;Dingding Wang;Tao Li
Affiliations:
School of Computing and Information Sciences, Florida International University, 11200 SW 8th St., Miami, FL 33199, USA.;School of Computing and Information Sciences, Florida International University, 11200 SW 8th St., Miami, FL 33199, USA.;School of Computing and Information Sciences, Florida International University, 11200 SW 8th St., Miami, FL 33199, USA
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2010

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Abstract

Many gene selection algorithms have been applied in gene expression data analysis successfully. To solve different developing environments of these toolkits, such as rankgene (Su et al., 2003), and mRMR(http: //research.janelia.org/peng/proj/mrmr/index.htm), perform data analysis and make algorithm comparison more flexible, we have developed a software package LIBGS including: seven new gene selection algorithms implemented using MATLAB; a MATLAB interface for Rankgene; a MATLAB interface for LIBSVM and WEKA; programs for converting data formats; a collection of six popular gene expression data sets. These features make LIBGS a useful tool in gene expression analysis and feature selection.