Selecting informative genes from microarray data by using a cyclic GA-based method

Mohd Saberi Mohamad, Sigeru Omatu, Safaai Deris, Michifumi Yoshioka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Microarray data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. The main problem that needs to be addressed is the selection of a small subset of genes from the thousands of genes in the data that contributes to a cancer disease. This selection process is difficult due to the availability of a small number of samples compared to the huge number of genes, many irrelevant genes, and noisy genes. Therefore, this paper proposes a cyclic method based on genetic algorithms (GA) to select a near-optimal (small) subset of informative genes that is relevant for cancer classification. The performance of the proposed method was evaluated by three benchmark microarray data sets and obtained encouraging results as compared with other experimented methods and previous related works.

Original languageEnglish
Title of host publicationISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation
Pages15-20
Number of pages6
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventUKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010 - Liverpool, United Kingdom
Duration: Jan 27 2010Jan 29 2010

Publication series

NameISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation

Conference

ConferenceUKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010
Country/TerritoryUnited Kingdom
CityLiverpool
Period1/27/101/29/10

Keywords

  • Component
  • Cyclic approach
  • Gene selection
  • Genetic algorithms
  • Hybrid method
  • Microarray data

ASJC Scopus subject areas

  • General Computer Science
  • Theoretical Computer Science

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