Citation

Kamarudin, Mizan and Ong, Chia Sui and Tan, Shing Chiang (2022) Quantum-Inspired Differential Evolution Algorithm in Probiotics Marker Genes Selection. In: 2022 10th International Conference on Information and Communication Technology (ICoICT), 2-3 August 2022, Bandung, Indonesia.

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Abstract

Selected microbial strains have long been used as probiotics for their health-promoting benefits. Genome analysis offers a faster and comprehensive approach for the screening of the probiotic potential of a microbial strain. Use of machine learning algorithm increases the applicability and reliability to perform prediction using genomic features. In this work, a metaheuristic algorithm, the quantum-inspired differential evolution (QDE) algorithm, was employed for probiotic marker genes selection. The genome data of 60 Bacillus spp. strains were annotated and represented with a standard identifier, the K numbers. By classifying the strains into probiotics (27 strains) and non-probiotics (33 strains), the elitist QDE algorithm was used to select a subset of features that can classify the strains into the correct class, with accuracy of 0.9055. A set of 45 features (K numbers) were shortlisted to be useful marker genes for probiotics potential.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Feature selection, quantum-inspired differential evolution, probiotics, genetic markers
Subjects:	R Medicine > RM Therapeutics. Pharmacology
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	30 Nov 2022 04:33
Last Modified:	30 Nov 2022 04:33
URII:	http://shdl.mmu.edu.my/id/eprint/10759

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