ArticleComputational and structural biotechnology journal2024
Exploring sperm cell motion dynamics: Insights from genetic algorithm-based analysis.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Elucidating motion patterns in sperm cell motion with dynamic mode decomposition.Journal of biological physics · 2026Article
- Deep Learning Models for Multi-Part Morphological Segmentation and Evaluation of Live Unstained Human Sperm.Sensors (Basel, Switzerland) · 2025Article
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4 authors.
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Abstract
Accurate analysis of sperm cell flagellar dynamics plays a crucial role in understanding sperm motility as flagella parameters determine cell behavior in the spatiotemporal domain. In this study, we introduce a novel approach by harnessing Genetic Algorithms (GA) to analyze sperm flagellar motion characteristics and compare the results with the traditional decomposition method based on Fourier analysis. Our analysis focuses on extracting key parameters of the equation approximating flagellar shape, including beating period time, bending amplitude, mean curvature, and wavelength. Additionally, we delve into the extraction of phase constants and initial swimming directions, vital for the comprehensive study of sperm cell pairs and bundling phenomena. One significant advantage of GA over Fourier analysis is its ability to integrate sperm cell motion data, enabling a more comprehensive analysis. In contrast, Fourier analysis neglects sperm cell motion by transitioning to a sperm-centered coordinate system (material system). In our comparative study, GA consistently outperform the Fourier analysis-based method, yielding a remarkable reduction in fitting error of up to 70% and on average by 45%. An in-depth exploration of the sperm cell motion becomes indispensable in a wide range of applications from complexities of reproductive biology and medicine, to developing soft flagellated microrobots.
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