Gene selection in microarray data from multi-objective perspective

Shahram Sabzevari, Salwani Abdullah

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

1 Citation (Scopus)

Abstract

Microarray technology provides a platform to study expression level of thousands of genes simultaneously, but its high dimensionality and noisy nature forces the usage of dimensionality reduction techniques. Among these techniques feature selection seems to be more favorable due to its goal to preserve feature semantic. Feature selection is also called gene selection while applied to genetic data. Inherently, gene selection objectives are manifold which makes it a proper candidate for multi-objective optimization. There are three different ways to deal with fitness evaluation in multi-objective literature. Between these three the Pareto base approach seems to deliver more promising advantages to the biologist, but it did not grab that much attention till now, probably due to its computational complexity. The intention of this paper is to provide an insight to gene selection problem from multi-objective perspective. Although, covering all the proposed methods are impossible, but hopefully those algorithms discussed here are enough to show the common trend in multi-objective gene selection in microarray data.

Original languageEnglish
Title of host publicationConference on Data Mining and Optimization
Pages199-207
Number of pages9
DOIs
Publication statusPublished - 2011
Event2011 3rd Conference on Data Mining and Optimization, DMO 2011 - Putrajaya
Duration: 28 Jun 201129 Jun 2011

Other

Other2011 3rd Conference on Data Mining and Optimization, DMO 2011
CityPutrajaya
Period28/6/1129/6/11

Fingerprint

Microarrays
Genes
Feature extraction
Multiobjective optimization
Computational complexity
Semantics

Keywords

  • Feature selection
  • Gene selection
  • Microarray
  • Multi-objective optimization
  • Pareto optimality

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

Cite this

Sabzevari, S., & Abdullah, S. (2011). Gene selection in microarray data from multi-objective perspective. In Conference on Data Mining and Optimization (pp. 199-207). [5976528] https://doi.org/10.1109/DMO.2011.5976528

Gene selection in microarray data from multi-objective perspective. / Sabzevari, Shahram; Abdullah, Salwani.

Conference on Data Mining and Optimization. 2011. p. 199-207 5976528.

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

Sabzevari, S & Abdullah, S 2011, Gene selection in microarray data from multi-objective perspective. in Conference on Data Mining and Optimization., 5976528, pp. 199-207, 2011 3rd Conference on Data Mining and Optimization, DMO 2011, Putrajaya, 28/6/11. https://doi.org/10.1109/DMO.2011.5976528
Sabzevari S, Abdullah S. Gene selection in microarray data from multi-objective perspective. In Conference on Data Mining and Optimization. 2011. p. 199-207. 5976528 https://doi.org/10.1109/DMO.2011.5976528
Sabzevari, Shahram ; Abdullah, Salwani. / Gene selection in microarray data from multi-objective perspective. Conference on Data Mining and Optimization. 2011. pp. 199-207
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