Application of machine learning in drug design

机译：机器学习在药物设计中的应用

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Neural networks and machine learning are two methods that are increasingly being used to model Structure Activity Relationships (SARs). These new methods make few statistical assumptions and are non-linear and nonparametric. We describe back-propagation from the field of neural networks, and Progol from machine learning, and illustrate their learning mechanisms using a simple expository problem.

机译：神经网络和机器学习是越来越多地用于对结构活动关系（SAR）进行建模的两种方法。这些新方法几乎没有统计假设，而且是非线性和非参数的。我们描述了来自神经网络领域的反向传播，以及来自机器学习的Progol，并使用一个简单的问题阐述了它们的学习机制。

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《NATO Advanced Study Institute on Experimental and Computational Approaches to Structure-Based Drug Design May 9-19, 1996 Erice, Sicily, Italy》|1996年|p.53-63|共11页
会议地点 Erice(IT)
作者
Ross D. King;
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原文格式 PDF
正文语种 eng
中图分类药学;
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Application of machine learning in drug design

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