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SYSTEMS AND METHODS FOR PREDICTING THE OLFACTORY PROPERTIES OF MOLECULES USING MACHINE LEARNING

机译:使用机器学习预测分子的嗅觉特性的系统和方法

摘要

The present disclosure provides systems and methods for predicting olfactory properties of a molecule. One example method includes obtaining a machine-learned graph neural network trained to predict olfactory properties of molecules based at least in part on chemical structure data associated with the molecules. The method includes obtaining a graph that graphically describes a chemical structure of a selected molecule. The method includes providing the graph as input to the machine-learned graph neural network. The method includes receiving prediction data descriptive of one or more predicted olfactory properties of the selected molecule as an output of the machine-learned graph neural network. The method includes providing the prediction data descriptive of the one or more predicted olfactory properties of the selected molecule as an output.
机译:本公开提供了用于预测分子的嗅觉特性的系统和方法。一种示例方法包括获得机器学习的图神经网络,其被训练为至少部分地基于与分子相关的化学结构数据来预测分子的嗅觉特性。该方法包括获得图形地描述所选分子的化学结构的图。该方法包括将图作为输入提供给机器学习图神经网络。该方法包括接收描述了所选分子的一个或多个预测的嗅觉特性的预测数据作为机器学习图神经网络的输出。该方法包括提供描述所选分子的一个或多个预测的嗅觉特性的预测数据作为输出。

著录项

  • 公开/公告号WO2020163860A1

    专利类型

  • 公开/公告日2020-08-13

    原文格式PDF

  • 申请/专利权人 GOOGLE LLC;

    申请/专利号WO2020US17477

  • 申请日2020-02-10

  • 分类号G16C20/30;G06N3/04;G06N3/08;G06N3/12;G06N5;G16C20/70;

  • 国家 WO

  • 入库时间 2022-08-21 11:09:50

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