Relevant gene selection using ANOVA-ant colony optimisation approach for malaria vector data classification
by Micheal Olaolu Arowolo; Joseph Bamidele Awotunde; Peace Ayegba; Shakirat Oluwatosin Haroon-Sulyman
International Journal of Modelling, Identification and Control (IJMIC), Vol. 41, No. 1/2, 2022

Abstract: Recent progress in gene expression data research makes it possible to quantify and identify several thousand genes' expressions simultaneously. For malaria infection and transmission, gene expression data classification using dimensionality reduction is a standard approach in gene expression data analysis and proposed for this study. A major problem occurs in the reduction of high dimensional data, it plays a significant role in improving the precision of classification, allowing biologists and clinicians to correctly predict infections in humans by choosing a limited subclass of appropriate genes and deleting redundant, and noisy genes. The combination of a novel analysis of variance (ANOVA) with ant colony optimisation (ACO) approach as a hybrid feature selection to select relevant genes is suggested in this study to minimise the redundancy between genes, and SVM is used for classification. The proposed method's efficacy was shown by the experimental outcomes based on the high-dimensional of gene expression data.

Online publication date: Tue, 22-Nov-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email