Integrating biological information for feature selection in microarray data classification

Ong Huey Fang; Norwati Mustapha; Md Nasir Sulaiman

doi:10.1109/ICCEA.2010.215

Integrating biological information for feature selection in microarray data classification

Ong Huey Fang, Norwati Mustapha, Md Nasir Sulaiman

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

10 Citations (Scopus)

Abstract

Due to the high dimensionality of microarray data, feature selection is an indispensable task in classification to identify a smaller subset of relevant genes. However, feature selection techniques that consider solely on gene expression values might not be able to identify biologically meaningful genes. Thus, this paper presents an integrative feature selection method that is able to incorporate gene expression data with additional biological data for finding informative genes. The proposed approach is a two-stage method that combined the strength of both filter method and association analysis. The experimental results show that the selected gene subsets are able to improve classification accuracy.

Original language	English
Title of host publication	2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
Pages	330-334
Number of pages	5
DOIs	https://doi.org/10.1109/ICCEA.2010.215
Publication status	Published - 2010
Externally published	Yes
Event	International Conference on Computer Engineering and Applications 2010 - Bali Island, Indonesia Duration: 19 Mar 2010 → 21 Mar 2010 Conference number: 2nd https://ieeexplore.ieee.org/xpl/conhome/5445539/proceeding (Proceedings)

Publication series

Name	2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
Volume	2

Conference

Conference	International Conference on Computer Engineering and Applications 2010
Abbreviated title	ICCEA 2010
Country/Territory	Indonesia
City	Bali Island
Period	19/03/10 → 21/03/10
Internet address	https://ieeexplore.ieee.org/xpl/conhome/5445539/proceeding (Proceedings)

Keywords

Classification
Data mining
Feature selection
Microarray

Access to Document

10.1109/ICCEA.2010.215

Cite this

Fang, O. H., Mustapha, N., & Sulaiman, M. N. (2010). Integrating biological information for feature selection in microarray data classification. In 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010 (pp. 330-334). (2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010; Vol. 2). https://doi.org/10.1109/ICCEA.2010.215

@inproceedings{5d802e67536c4d349c48cb87a568b529,

title = "Integrating biological information for feature selection in microarray data classification",

abstract = "Due to the high dimensionality of microarray data, feature selection is an indispensable task in classification to identify a smaller subset of relevant genes. However, feature selection techniques that consider solely on gene expression values might not be able to identify biologically meaningful genes. Thus, this paper presents an integrative feature selection method that is able to incorporate gene expression data with additional biological data for finding informative genes. The proposed approach is a two-stage method that combined the strength of both filter method and association analysis. The experimental results show that the selected gene subsets are able to improve classification accuracy.",

keywords = "Classification, Data mining, Feature selection, Microarray",

author = "Fang, {Ong Huey} and Norwati Mustapha and Sulaiman, {Md Nasir}",

note = "Copyright: Copyright 2010 Elsevier B.V., All rights reserved.; International Conference on Computer Engineering and Applications 2010, ICCEA 2010 ; Conference date: 19-03-2010 Through 21-03-2010",

year = "2010",

doi = "10.1109/ICCEA.2010.215",

language = "English",

isbn = "9780769539829",

series = "2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010",

pages = "330--334",

booktitle = "2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010",

url = "https://ieeexplore.ieee.org/xpl/conhome/5445539/proceeding",

}

Fang, OH, Mustapha, N & Sulaiman, MN 2010, Integrating biological information for feature selection in microarray data classification. in 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010. 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010, vol. 2, pp. 330-334, International Conference on Computer Engineering and Applications 2010, Bali Island, Indonesia, 19/03/10. https://doi.org/10.1109/ICCEA.2010.215

Integrating biological information for feature selection in microarray data classification. / Fang, Ong Huey; Mustapha, Norwati; Sulaiman, Md Nasir.

2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010. 2010. p. 330-334 (2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Integrating biological information for feature selection in microarray data classification

AU - Fang, Ong Huey

AU - Mustapha, Norwati

AU - Sulaiman, Md Nasir

N1 - Conference code: 2nd

PY - 2010

Y1 - 2010

N2 - Due to the high dimensionality of microarray data, feature selection is an indispensable task in classification to identify a smaller subset of relevant genes. However, feature selection techniques that consider solely on gene expression values might not be able to identify biologically meaningful genes. Thus, this paper presents an integrative feature selection method that is able to incorporate gene expression data with additional biological data for finding informative genes. The proposed approach is a two-stage method that combined the strength of both filter method and association analysis. The experimental results show that the selected gene subsets are able to improve classification accuracy.

AB - Due to the high dimensionality of microarray data, feature selection is an indispensable task in classification to identify a smaller subset of relevant genes. However, feature selection techniques that consider solely on gene expression values might not be able to identify biologically meaningful genes. Thus, this paper presents an integrative feature selection method that is able to incorporate gene expression data with additional biological data for finding informative genes. The proposed approach is a two-stage method that combined the strength of both filter method and association analysis. The experimental results show that the selected gene subsets are able to improve classification accuracy.

KW - Classification

KW - Data mining

KW - Feature selection

KW - Microarray

UR - http://www.scopus.com/inward/record.url?scp=77952761322&partnerID=8YFLogxK

U2 - 10.1109/ICCEA.2010.215

DO - 10.1109/ICCEA.2010.215

M3 - Conference Paper

AN - SCOPUS:77952761322

SN - 9780769539829

T3 - 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010

SP - 330

EP - 334

BT - 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010

T2 - International Conference on Computer Engineering and Applications 2010

Y2 - 19 March 2010 through 21 March 2010

ER -

Integrating biological information for feature selection in microarray data classification

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Cite this