Record Details

Autism Gene Subset Selection from Microarray data – A Wrapper Approach

NOPR - NISCAIR Online Periodicals Repository

View Archive Info
 
 
Field Value
 
Title Autism Gene Subset Selection from Microarray data – A Wrapper Approach
 
Creator G, Anurekha
P, Geetha
 
Subject Autism spectrum disorder
Dimensionality reduction
Feature selection
Meta-heuristic
Whale optimization algorithm
 
Description 841-850
Autism spectrum disorder is a complex neurodevelopment disorder that affects an individual's social behavior.
Microarray analysis is an extensively used technique to detect autism. Microarray data can provide additional insight into
the etiology of the disorder. Identifying the specific set of genes associated with autism from complex microarray data poses
a significant research challenge due to its high dimensionality. However, Gene subset selection is classified as an np-hard
problem that can be handled by the meta-heuristic algorithm. In this paper, a novel meta-heuristic Game Theory Based
Whale Optimization Algorithm is proposed. The proposed algorithm uses a two-person zero-sum game theory and
convergence parameter to increase convergence rate and avoid local optima. The performance of the proposed algorithm is
tested with 23 mathematical benchmark functions and compared with other state-of-the-art algorithms. Further, the proposed
algorithm is employed as a wrapper-based gene subset selection model with a support vector machine. Furthermore, the
outcomes demonstrate that the gene selection model utilizing a wrapper-based approach is capable of effectively identifying
a subset of autism-related genes with desirable accuracy.
 
Date 2023-08-09T04:27:37Z
2023-08-09T04:27:37Z
2023-08
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/62412
https://doi.org/10.56042/jsir.v82i08.3398
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.82(08) [August 2023]