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Updated: Feb 17, 2026

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KmPred:使用集成机器学习框架预测迈凯利斯常数 (Km)

Meshari Alazmi1

  • 1College of Computer Science and Engineering, University of Ha'il, Ha'il, Saudi Arabia.

Frontiers in artificial intelligence
|February 16, 2026
PubMed
概括

这项研究介绍了KmPred,这是一个用于预测酶基质亲和力 (Km) 的机器学习框架. KmPred将蛋白质序列数据与基质分子描述器集成在一起,为酶动力学建模提供了传统体外测试的更快的替代方案.

关键词:
在KmPred之前迈凯利斯门顿常数 (Km)生物信息学是一种生物信息学.发现药物的发现.代谢工程是代谢工程.分子描述器 分子描述器蛋白质嵌入物 蛋白质嵌入物系统生物学 系统生物学

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