A mathematical programming approach for gene selection and tissue classification | Zendy

Minghe Sun | Zendy; Momiao Xiong | Zendy

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A mathematical programming approach for gene selection and tissue classification

Author(s) -

Minghe Sun,

Momiao Xiong

Publication year - 2003

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/btg145

Subject(s) - selection (genetic algorithm) , integer programming , computer science , gene selection , gene expression programming , genetic programming , data mining , variety (cybernetics) , parametric statistics , machine learning , parametric programming , artificial intelligence , microarray analysis techniques , algorithm , mathematics , gene , gene expression , biology , statistics , biochemistry

Extracting useful information from expression levels of thousands of genes generated with microarray technology needs a variety of analytical techniques. Mathematical programming approaches for classification analysis outperform parametric methods when the data depart from assumptions underlying these methods. Therefore, a mathematical programming approach is developed for gene selection and tissue classification using gene expression profiles.

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