- author = "Shin Ando and Hitoshi Iba",
- title = "Classification of Gene Expression Profile Using Combinatory Method of Evolutionary Computation and Machine Learning",
- journal = "Genetic Programming and Evolvable Machines",
- year = "2004",
- volume = "5",
- number = "2",
- pages = "145--156",
- month = jun,
- keywords = "genetic algorithms, genetic programming, evolutionary computation, artificial immune system, wrapper approach, gene expression classification, cancer diagnosis",
- ISSN = "1389-2576",
-
DOI = "
doi:10.1023/B:GENP.0000023685.83861.69",
- abstract = "The analysis of large amount of gene expression profiles, which became available by rapidly developed monitoring tools, is an important task in Bioinformatics. The problem we address is the discrimination of gene expression profiles of different classes, such as cancerous/benign tissues. Two subtasks in such problem, feature subset selection and inductive learning has critical effect on each other. In the wrapper approach, combinatorial search of feature subset is done with performance of inductive learning as search criteria. This paper compares few combinations of supervised learning and combinatorial search when used in the wrapper approach. Also an extended GA implementation is introduced, which uses Clonal selection, a data-driven selection method. It compares very well to standard GA. The analysis of the obtained classifier reveals synergistic effect of genes in discrimination of the profiles.",
-
notes = "Part of \cite{banzhaf:2004:biogec} Special Issue on
Biological Applications of Genetic and Evolutionary
Computation Guest Editor(s): Wolfgang Banzhaf , James
Foster
(1) Department of Electronics, School of Engineering, University of Tokyo, Yokohama, Japan
(2) Department of Frontier Informatics, School of Frontier Science, University of Tokyo, Chiba, Japan",
