Optimal search-based gene subset selection for gene array cancer classification.

Optimal search-based gene subset selection for gene array cancer classification. Research Abstract Details 

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Optimal search-based gene subset selection for gene array cancer classification. Abstract Text:

Jiexun Li,Hua Su,Hsinchun Chen,Bernard W Futscher,

High dimensionality has been a major problem for gene array-based cancer classification. It is critical to identify marker genes for cancer diagnoses. We developed a framework of gene selection methods based on previous studies. This paper focuses on optimal search-based subset selection methods because they evaluate the group performance of genes and help to pinpoint global optimal set of marker genes. Notably, this paper is the first to introduce tabu search (TS) to gene selection from high-dimensional gene array data. Our comparative study of gene selection methods demonstrated the effectiveness of optimal search-based gene subset selection to identify cancer marker genes. TS was shown to be a promising tool for gene subset selection.

Optimal search-based gene subset selection for gene array cancer classification. Publishing Authors By Initials

J Li,H Su,H Chen,BW Futscher,

For similar biological factors: biological markers: tumor markers, biological research abstracts see: biological factors: biological markers: tumor markers, biological research

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Optimal search-based gene subset selection for gene array cancer classification. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: IEEE transactions on information technology in bio

VOLUME: 11

Page Numbers: 398-405

Journal Abbreviation:

ISSN: 1089-7771

DAY: 3

MONTH: Jul

YEAR: 2007

Optimal search-based gene subset selection for gene array cancer classification. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 9712259

Optimal search-based gene subset selection for gene array cancer classification. Keywords Mesh Terms:

KEYWORDS: Tumor Markers, Biological

MESH TERMS: classification

Chemical & Substance for Abstract: Optimal search-based gene subset selection for gene array cancer classification. Information

Substance Name: Tumor Markers, Biological

Registry Number: 0

Grant and Affiliation Information for Optimal search-based gene subset selection for gene array cancer classification.

AFFILIATION: Artificial Intelligence Laboratory, Department of Management Information Systems, Eller College of Management, University of Arizona, Tucson, AZ 85721, USA. jiexun@eller.arizona.edu

Country: United States

AGENCY: United States NLM

GRANT: R33 LM07299-01

ACRONYM: LM

MEDLINETA: IEEE Trans Inf Technol Biomed

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