Comparative study on machine learning algorithm prediction of soybean protein localization

Zhiqiang Liu; Yulan Tang

doi:10.1117/12.3045037

16 January 2025 Comparative study on machine learning algorithm prediction of soybean protein localization

Zhiqiang Liu, Yulan Tang

Author Affiliations +

Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 134472P (2025) https://doi.org/10.1117/12.3045037
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China

Abstract

Soybean protein is one of the important components of modern human diet. How to accurately and quickly determine the location of soybean protein is the main topic of research scholars. In order to understand the soybean genome, improve human dietary health behavior, explore effective methods of soybean protein subcellular localization prediction with different deletion degrees, and improve the level of soybean protein subcellular localization prediction, this paper aims to understand the current situation of machine learning algorithms and applications and, according to the research and application characteristics of protein localization technology in the new era, this paper mainly discusses the application advantages of four kinds of machine learning algorithms in predicting soybean protein localization, so as to provide technical support for soybean protein data prediction analysis.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhiqiang Liu and Yulan Tang "Comparative study on machine learning algorithm prediction of soybean protein localization", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 134472P (16 January 2025); https://doi.org/10.1117/12.3045037

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