Support vector machine classification and validation of cancer tissue samples using microarray expression data | Zendy

Terrence S. Furey | Zendy; Nello Cristianini | Zendy; Nigel Duffy | Zendy; David Bednarski | Zendy; Michèl Schummer | Zendy; David Haussler | Zendy

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Support vector machine classification and validation of cancer tissue samples using microarray expression data

Author(s) -

Terrence S. Furey,

Nello Cristianini,

Nigel Duffy,

David Bednarski,

Michèl Schummer,

David Haussler

Publication year - 2000

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/16.10.906

Subject(s) - support vector machine , computer science , outlier , artificial intelligence , classifier (uml) , robustness (evolution) , microarray analysis techniques , pattern recognition (psychology) , data mining , computational biology , gene expression , bioinformatics , biology , gene , genetics

DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results.

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