Microarray data analysis using rival penalized em algorithm in normal mixture models

Xing Ming Zhao; Yiu Ming Cheung; De Shuang Huang

Microarray data analysis using rival penalized em algorithm in normal mixture models

Xing Ming Zhao^*, Yiu Ming Cheung, De Shuang Huang

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

2 Citations (Scopus)

Abstract

Microarray technology is a useful tool for monitoring the expressed levels of thousands of genes simultaneously. Recently, mixture modelling has been used to extract information from expressed genes. It utilizes two separate steps to estimate the number of classes and model parameters, respectively, which however may be time-consuming and fall into sub-optimal solutions. In this paper, we therefore apply an one-step approach, namely Rival Penalized Expectation-Maximization (RPEM) algorithm, to microarray data analysis. The RPEM algorithm is capable of estimating the parameters of the normal mixture model, meanwhile determining the number of classes automatically. The numerical results have shown the effectiveness of this technique on real microarray data analysis.

Original language	English
Title of host publication	Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005
Pages	35-38
Number of pages	4
Publication status	Published - 2005
Event	2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005 - Suzhou, China Duration: 28 May 2005 → 30 May 2005

Publication series

Name	Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005

Conference

Conference	2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005
Country/Territory	China
City	Suzhou
Period	28/05/05 → 30/05/05

Scopus Subject Areas

General Engineering

Cite this

@inproceedings{9aa33e78b5da4b69bf324c8aff1328c9,

title = "Microarray data analysis using rival penalized em algorithm in normal mixture models",

abstract = "Microarray technology is a useful tool for monitoring the expressed levels of thousands of genes simultaneously. Recently, mixture modelling has been used to extract information from expressed genes. It utilizes two separate steps to estimate the number of classes and model parameters, respectively, which however may be time-consuming and fall into sub-optimal solutions. In this paper, we therefore apply an one-step approach, namely Rival Penalized Expectation-Maximization (RPEM) algorithm, to microarray data analysis. The RPEM algorithm is capable of estimating the parameters of the normal mixture model, meanwhile determining the number of classes automatically. The numerical results have shown the effectiveness of this technique on real microarray data analysis.",

author = "Zhao, {Xing Ming} and Cheung, {Yiu Ming} and Huang, {De Shuang}",

note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005 ; Conference date: 28-05-2005 Through 30-05-2005",

year = "2005",

language = "English",

isbn = "0780390067",

series = "Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005",

pages = "35--38",

booktitle = "Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005",

}

Zhao, XM, Cheung, YM & Huang, DS 2005, Microarray data analysis using rival penalized em algorithm in normal mixture models. in Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005. Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005, pp. 35-38, 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005, Suzhou, China, 28/05/05.

Microarray data analysis using rival penalized em algorithm in normal mixture models. / Zhao, Xing Ming; Cheung, Yiu Ming; Huang, De Shuang.
Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005. 2005. p. 35-38 (Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Microarray data analysis using rival penalized em algorithm in normal mixture models

AU - Zhao, Xing Ming

AU - Cheung, Yiu Ming

AU - Huang, De Shuang

PY - 2005

Y1 - 2005

N2 - Microarray technology is a useful tool for monitoring the expressed levels of thousands of genes simultaneously. Recently, mixture modelling has been used to extract information from expressed genes. It utilizes two separate steps to estimate the number of classes and model parameters, respectively, which however may be time-consuming and fall into sub-optimal solutions. In this paper, we therefore apply an one-step approach, namely Rival Penalized Expectation-Maximization (RPEM) algorithm, to microarray data analysis. The RPEM algorithm is capable of estimating the parameters of the normal mixture model, meanwhile determining the number of classes automatically. The numerical results have shown the effectiveness of this technique on real microarray data analysis.

AB - Microarray technology is a useful tool for monitoring the expressed levels of thousands of genes simultaneously. Recently, mixture modelling has been used to extract information from expressed genes. It utilizes two separate steps to estimate the number of classes and model parameters, respectively, which however may be time-consuming and fall into sub-optimal solutions. In this paper, we therefore apply an one-step approach, namely Rival Penalized Expectation-Maximization (RPEM) algorithm, to microarray data analysis. The RPEM algorithm is capable of estimating the parameters of the normal mixture model, meanwhile determining the number of classes automatically. The numerical results have shown the effectiveness of this technique on real microarray data analysis.

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M3 - Conference proceeding

AN - SCOPUS:23844476524

SN - 0780390067

T3 - Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005

SP - 35

EP - 38

BT - Proceedings of the 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005

T2 - 2005 IEEE International Workshop on VLSI Design and Video Technology, IWVDVT 2005

Y2 - 28 May 2005 through 30 May 2005

ER -

Microarray data analysis using rival penalized em algorithm in normal mixture models

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