Gene selection algorithms for microarray data based on least squares support vector machine

BMC Bioinformatics
E Ke TangXin Yao

Abstract

In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary to conduct the discriminant analysis with all the genes. Hence, gene selection is usually performed to select important genes. A gene selection method searches for an optimal or near optimal subset of genes with respect to a given evaluation criterion. In this paper, we propose a new evaluation criterion, named the leave-one-out calculation (LOOC, A list of abbreviations appears just above the list of references) measure. A gene selection method, named leave-one-out calculation sequential forward selection (LOOCSFS) algorithm, is then presented by combining the LOOC measure with the sequential forward selection scheme. Further, a novel gene selection algorithm, the gradient-based leave-one-out gene selection (GLGS) algorithm, is also proposed. Both of the gene selection algorithms originate from an efficient and exact calculation of the leave-one-out cross-validation error of the least squares support vector machine (LS-SVM). The proposed approaches are applied to two microarray datasets and compared to other well-known gene selection methods using codes available...Continue Reading

References

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Citations

Jan 6, 2010·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Li-Yeh ChuangCheng-Hong Yang
Mar 15, 2012·Nucleic Acids Research·Jia ZengJianpeng Ma
Feb 4, 2009·BMC Bioinformatics·Pei-Chun ChenChuhsing K Hsiao
Sep 9, 2006·BMC Bioinformatics·Stuart G Baker, Barnett S Kramer
Jul 25, 2009·BMC Genomics·Qingzhong LiuYouping Deng
May 4, 2012·Algorithms for Molecular Biology : AMB·Tapio PahikkalaTero Aittokallio
Nov 4, 2009·IEEE Transactions on Nanobioscience·Piyushkumar A Mundra, Jagath C Rajapakse
Jul 15, 2015·Advances in Bioinformatics·Zena M Hira, Duncan F Gillies
Feb 14, 2018·Journal of Magnetic Resonance Imaging : JMRI·Jing WangYu-Dong Zhang
Oct 5, 2007·BMC Bioinformatics·Ji-Gang Zhang, Hong-Wen Deng

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Datasets Mentioned

BETA
AB007960
191
AF070546
AB028964
AJ010228
AB020678

Methods Mentioned

BETA
PCA

Software Mentioned

SVMlab
MathType
LS
GLGS
Matlab
LOOCSFS

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