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Biomarker Identification and Cancer Classification Based on Microarray Data Using Laplace Naive Bayes Model with Mean Shrinkage

Authors:

Xiao-Fei ZhangAuthors Info & Claims

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 9, Issue 6

Pages 1649 - 1662

https://doi.org/10.1109/TCBB.2012.105

Published: 01 November 2012 Publication History

Abstract

Biomarker identification and cancer classification are two closely related problems. In gene expression data sets, the correlation between genes can be high when they share the same biological pathway. Moreover, the gene expression data sets may contain outliers due to either chemical or electrical reasons. A good gene selection method should take group effects into account and be robust to outliers. In this paper, we propose a Laplace naive Bayes model with mean shrinkage (LNB-MS). The Laplace distribution instead of the normal distribution is used as the conditional distribution of the samples for the reasons that it is less sensitive to outliers and has been applied in many fields. The key technique is the L_1 penalty imposed on the mean of each class to achieve automatic feature selection. The objective function of the proposed model is a piecewise linear function with respect to the mean of each class, of which the optimal value can be evaluated at the breakpoints simply. An efficient algorithm is designed to estimate the parameters in the model. A new strategy that uses the number of selected features to control the regularization parameter is introduced. Experimental results on simulated data sets and 17 publicly available cancer data sets attest to the accuracy, sparsity, efficiency, and robustness of the proposed algorithm. Many biomarkers identified with our method have been verified in biochemical or biomedical research. The analysis of biological and functional correlation of the genes based on Gene Ontology (GO) terms shows that the proposed method guarantees the selection of highly correlated genes simultaneously.

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Mollah AAsad E(2021)Biomarker Identification From Gene Expression Based on Symmetrical UncertaintyInternational Journal of Intelligent Information Technologies10.4018/IJIIT.28996617:4(1-19)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.4018/IJIIT.289966
Pattanateepapon ASuwansantisuk WKumhom P(2021)Methods to transform microarray data for cancer prediction2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)10.1109/CIBCB.2016.7758104(1-7)Online publication date: 10-Mar-2021
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Boucheham ABatouche M(2017)Hybrid Wrapper/Filter Gene Selection Using an Ensemble of Classifiers and PSO AlgorithmInternational Journal of Applied Metaheuristic Computing10.4018/IJAMC.20170401028:2(22-37)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.4018/IJAMC.2017040102
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Biomarker Identification and Cancer Classification Based on Microarray Data Using Laplace Naive Bayes Model with Mean Shrinkage

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cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics

IEEE/ACM Transactions on Computational Biology and Bioinformatics Volume 9, Issue 6

November 2012

302 pages

ISSN:1545-5963

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IEEE Computer Society Press

Washington, DC, United States

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Published: 01 November 2012

Published in�TCBB�Volume 9, Issue 6

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Cited By

Mollah AAsad E(2021)Biomarker Identification From Gene Expression Based on Symmetrical UncertaintyInternational Journal of Intelligent Information Technologies10.4018/IJIIT.28996617:4(1-19)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.4018/IJIIT.289966
Pattanateepapon ASuwansantisuk WKumhom P(2021)Methods to transform microarray data for cancer prediction2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)10.1109/CIBCB.2016.7758104(1-7)Online publication date: 10-Mar-2021
https://dl.acm.org/doi/10.1109/CIBCB.2016.7758104
Boucheham ABatouche M(2017)Hybrid Wrapper/Filter Gene Selection Using an Ensemble of Classifiers and PSO AlgorithmInternational Journal of Applied Metaheuristic Computing10.4018/IJAMC.20170401028:2(22-37)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.4018/IJAMC.2017040102
Lovato PBicego MKesa MJojic NMurino VPerina A(2016)Traveling on discrete embeddings of gene expressionArtificial Intelligence in Medicine10.1016/j.artmed.2016.05.00270:C(1-11)Online publication date: 1-Jun-2016
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Rathore SHussain MKhan A(2014)GECCIEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)10.1109/TCBB.2014.234465511:6(1131-1145)Online publication date: 1-Nov-2014
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