Genetic algorithms applied to multi-class prediction for the analysis of gene expression data | Zendy

Chia-Huey Ooi | Zendy; Patrick Tan | Zendy

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Genetic algorithms applied to multi-class prediction for the analysis of gene expression data

Author(s) -

Chia-Huey Ooi,

Patrick Tan

Publication year - 2002

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/19.1.37

Subject(s) - computer science , classifier (uml) , data mining , feature selection , machine learning , class (philosophy) , artificial intelligence , selection (genetic algorithm) , genetic algorithm , algorithm

An important challenge in the use of large-scale gene expression data for biological classification occurs when the expression dataset being analyzed involves multiple classes. Key issues that need to be addressed under such circumstances are the efficient selection of good predictive gene groups from datasets that are inherently 'noisy', and the development of new methodologies that can enhance the successful classification of these complex datasets.

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