Hybridising harmony search with a Markov blanket for gene selection problems

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Gene selection, which is a well-known NP-hard problem, is a challenging task that has been the subject of a large amount of research, especially in relation to classification tasks. This problem addresses the identification of the smallest possible set of genes that could achieve good predictive performance. Many gene selection algorithms have been proposed; however, because the search space increases exponentially with the number of genes, finding the best possible approach for a solution that would limit the search space is crucial. Metaheuristic approaches have the ability to discover a promising area without exploring the whole solution space. Hence, we propose a new method that hybridises the Harmony Search Algorithm (HSA) and the Markov Blanket (MB), called HSA-MB, for gene selection in classification problems. In this proposed approach, the HSA (as a wrapper approach) improvises a new harmony that is passed to the MB (treated as a filter approach) for further improvement. The addition and deletion of operators based on gene ranking information is used in the MB algorithm to further improve the harmony and to fine-tune the search space. The HSA-MB algorithm method works especially well on selected genes with higher correlation coefficients based on symmetrical uncertainty. Ten microarray datasets were experimented on, and the results demonstrate that the HSA-MB has a performance that is comparable to state-of-the-art approaches. HSA-MB yields very small sets of genes while preserving the classification accuracy. The results suggest that HSA-MB has a high potential for being an alternative method of gene selection when applied to microarray data and can be of benefit in clinical practice.

Original languageEnglish
Pages (from-to)108-121
Number of pages14
JournalInformation Sciences
Volume258
DOIs
Publication statusPublished - 10 Feb 2014

Fingerprint

Harmony Search
Gene Selection
Search Algorithm
Genes
Gene
Search Space
Microarrays
Wrapper
Harmony
NP-hard Problems
Microarray Data
Metaheuristics
Microarray
Classification Problems
Correlation coefficient
Deletion
Ranking
Filter
Computational complexity
Uncertainty

Keywords

  • Filter approach
  • Gene selection
  • Harmony search algorithm
  • Markov blanket
  • Wrapper approach

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management

Cite this

Hybridising harmony search with a Markov blanket for gene selection problems. / Shreem, Salam Salameh; Abdullah, Salwani; Ahmad Nazri, Mohd Zakree.

In: Information Sciences, Vol. 258, 10.02.2014, p. 108-121.

Research output: Contribution to journalArticle

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