Comparative study on machine learning algorithm prediction of soybean protein localization

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.