Molecular Marker Discovery for Ovarian Maturation Level of the Black Tiger Shrimp from Microarray Data Using Genetic Algorithm
Journal Title: International Journal of the Computer, the Internet and Management - Year 2019, Vol 27, Issue 2
Abstract
This paper proposes an embedded-based gene selection method in the black tiger shrimp microarray dataset using Genetic Algorithm (GA). Moreover, we analyze the effect of selected genes for ovarian maturation level in the term of biological perspective. We run experiment on 6 black tiger shrimp microarray datasets which were publically available. First, we run GA to find the optimized individual length. Next, the GA-based predictive model is run to predict the Gonadosomatic Index (GSI) of ovarian maturation level in black tiger shrimp. Finally, the most frequently selected genes from GA are observed and analyzed. The experimental results show that the optimized individual length for GA is 4 and the selected informative genes are from heart and gill tissues of black tiger shrimp.
Authors and Affiliations
Supoj Hengpraprohm, Suwimol Jungjit, Kairung Hengpraprohm, Dech Thammasiri
Keywords
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- EP ID EP604271
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