Title: Triclustering of gene expression microarray data using a hybrid bio-inspired approach

Authors: R. Balamurugan; Pushkar Nahar; Suyash Agarwal; S.P. Raja

Addresses: School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vellore-632014, Tamil nadu, India ' School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vellore-632014, Tamil nadu, India ' School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vellore-632014, Tamil nadu, India ' School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vellore-632014, Tamil nadu, India

Abstract: The triclustering of microarray genes contains a subset of genes that carry information about the behaviour of these genes under specific conditions over specific periods. In this paper, we present a meta-heuristic technique that is a hybrid cuckoo search algorithm used to solve the computationally intensive problem. In general, cuckoo search approach relies upon the fact that the cuckoo lays its eggs in the nest of host birds; however, if the egg is not identified and knocked down, the cuckoo's eggs are hatched. In this paper, we propose cuckoo search with harmony search for triclustering genes. In the experimental results on homo sapiens dataset, the proposed method yielded 0.12206 statistical difference from background. Moreover, this algorithm was evaluated over certain parameters and the experimental results outperformed other existing algorithms.

Keywords: triclustering; microarray; cuckoo search; optimisation; ontology.

DOI: 10.1504/IJCBDD.2023.133849

International Journal of Computational Biology and Drug Design, 2023 Vol.15 No.5, pp.430 - 444

Received: 01 Nov 2022
Accepted: 09 Mar 2023
Published online: 04 Oct 2023 *

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