| Literature DB >> 20681484 |
Yi Zhang1, Dingding Wang, Tao Li.
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: 1) Seven new gene selection algorithms implemented using MATLAB. 2) MATLAB interface for Rankgene. 3) MATLAB interface for LIBSVM and WEKA. 4) Programs for converting data formats. 5) A collection of six popular gene expression data sets. These features make LIBGS a useful tool in gene expression analysis and feature selection.Entities:
Mesh:
Year: 2010 PMID: 20681484 DOI: 10.1504/ijdmb.2010.033525
Source DB: PubMed Journal: Int J Data Min Bioinform ISSN: 1748-5673 Impact factor: 0.667