A hybrid of clustering and quantum genetic algorithm for relevant genes selection for cancer microarray data-Reference-Cited by-同舟云学术

A hybrid of clustering and quantum genetic algorithm for relevant genes selection for cancer microarray data

Published:2016-07-27 Issue:3 Volume:20 Page:161-173
ISSN:1327-2314
Container-title:International Journal of Knowledge-based and Intelligent Engineering Systems
language:
Short-container-title:KES

Author:

Sardana Manju¹,Agrawal R.K.²,Kaur Baljeet¹

Affiliation:

1. Hansraj College, University of Delhi, Delhi, India

2. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

Publisher

IOS Press

Subject

Artificial Intelligence,Control and Systems Engineering,Software

Reference74 articles.

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3. Alba E., Garca-Nieto J., Jourdan L. and Talbi E.G., A comparison of PSO and GA approaches for gene selection and classification of microarray data, in: Genetic and Evolutionary Computation Conference, ACM Press, (2007).

4. Alon U., Barkai N., Notterman D.A., Gish K., Ybarra S., Mack D. and Levine A.J., Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligo-nucleotide array, Proc Nat'l Academy of Science 9612 (1999), 6745-6750.

5. Varela-arrabal, microarray gene expression classification with few genes: Criteria to combine attribute selection and classification methods;Alonso-Gonzalez;Expert Systems with Applications,2012

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