SYSTEMS AND METHODS FOR IDENTIFYING ENTITIES THAT HAVE A TARGET PROPERTY
    1.
    发明申请
    SYSTEMS AND METHODS FOR IDENTIFYING ENTITIES THAT HAVE A TARGET PROPERTY 审中-公开
    用于识别具有目标属性的实体的系统和方法

    公开(公告)号:WO2017059250A1

    公开(公告)日:2017-04-06

    申请号:PCT/US2016/054777

    申请日:2016-09-30

    CPC classification number: G06N5/048 G06F19/10 G06N99/005

    Abstract: Systems and methods for assaying a test entity for a property, without measuring the property, are provided. Exemplary test entities include proteins, protein mixtures, and protein fragments. Measurements of first features in a respective subset of an N-dimensional space and of second features in a respective subset of an M-dimensional space, is obtained as training data for each reference in a plurality of reference entities. One or more of the second features is a metric for the target property. A subset of first features, or combinations thereof, is identified using feature selection. A model is trained on the subset of first features using the training data. Measurement values for the subset of first features for the test entity are applied to thereby obtaining a model value that is compared to model values obtained using measured values of the subset of first features from reference entities exhibiting the property.

    Abstract translation: 提供了用于测定属性的测试实体而不测量属性的系统和方法。 示例性测试实体包括蛋白质,蛋白质混合物和蛋白质片段。 作为用于多个参考实体中的每个参考的训练数据,获得N维空间的相应子集中的第一特征和M维空间的相应子集中的第二特征的度量。 第二个特征中的一个或多个是目标属性的度量。 使用特征选择来识别第一特征或其组合的子集。 使用训练数据对第一特征子集进行训练。 应用用于测试实体的第一特征的子集的测量值,从而获得与使用展示该属性的参考实体的第一特征子集的测量值获得的模型值进行比较的模型值。

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