从化学结构中预测艾姆斯测试结果的进展:从第一和第二艾姆斯/QSAR国际挑战项目中对模型的深入再评估

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Updated: Jul 3, 2025

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function
05:57

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Published on: April 26, 2024

391

Yoshihiro Uesawa1

  • 1Department of Medical Molecular Informatics, Meiji Pharmaceutical University, Tokyo 204-8588, Japan.

International journal of molecular sciences
|February 10, 2024
PubMed
概括

这项研究重新分析了艾姆斯/定量结构-活性关系 (QSAR) 挑战项目,确定了明治制药大学的MMI-VOTE1和MMI-STK1模型作为表现最好的模型. 这些发现澄清了艾姆斯预测技术的发现.

关键词:
艾姆斯试验的测试适用性领域 (applicability domain) 是一个应用领域.在Silico研究中的研究.机器学习是机器学习.预测性表现的预测性表现.定量结构 活动关系

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