AI-DRIVEN INSIGHTS INTO THE ROLE OF THE ACTN3 GENE IN MUSCLE STRENGTH AND SPRINT PERFORMANCE
DOI:
https://doi.org/10.29121/shodhkosh.v5.i7SE.2024.5852Keywords:
Actn3 Gene, Alpha-Actinin-3, R577x Polymorphism, Fast-Twitch Muscle Fibers, Sprint Performance, Muscle Strength, Artificial Intelligence, Machine Learning, Sports Genetics, Predictive Modeling, Talent Identification, Personalized Training, Gene-Environment Interaction, Athlete Performance OptimizationAbstract [English]
The ACTN3 gene, encoding the alpha-actinin-3 protein, plays a pivotal role in determining muscle performance, particularly in strength and sprint activities. The R577X polymorphism in the ACTN3 gene creates genetic variations that correlate with fast-twitch muscle fiber composition, influencing power, speed, and endurance. This study investigates the relationship between ACTN3 genotypes and athletic performance using Artificial Intelligence (AI). AI tools, including machine learning algorithms, predictive analytics, and data visualization, were employed to analyze a dataset of athlete profiles. Results reveal significant correlations between R allele carriers and enhanced sprint performance, while X allele homozygotes exhibited traits favoring endurance. AI-enabled models provided accurate performance predictions and uncovered complex gene-environment interactions. These findings highlight the transformative potential of AI in advancing sports genetics, paving the way for personalized training and talent identification strategies.
References
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Copyright (c) 2024 Dr. Madayya S/O. Basalingayya, Dr. Md Sayeeduddin
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