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The Index of Ideality of Correlation (IIC): model for sweetness

机译:相关性的思想指标(IIC):甜味模型

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The prediction of physicochemical and biochemical endpoints related to food, cosmetics, drug discovery, and medicine using computational approaches is relevant to the need of the modern society. The experimental determination of the endpoints is impossible for all necessary substances. The Index of Ideality of Correlation (IIC) is a criterion of predictive potential of a model. The index has been implemented in the CORAL software, which is a tool to build up quantitative structureactivity relationships. In the present work, two models for sweetness potential are built using this software. The first model is built without taking into account the IIC. The second model is built with taking into account the IIC. The results show that the IIC improves the predictive potential. This was confirmed in three computational experiments with random splits of the data related to sweetness into training and validation sets.
机译:使用计算方法的食品,化妆品,药物发现和药物有关的物理化学和生化终点的预测与现代社会的需要有关。 对所有必要物质不可能进行终点的实验测定。 相关性的思维(IIC)是模型的预测潜力的标准。 该索引已在珊瑚软件中实现,这是一种构建定量结构性关系的工具。 在目前的工作中,使用该软件建立了两个甜度潜力的模型。 第一个模型是建立的,而不考虑IIC。 通过考虑到IIC,建立了第二种模型。 结果表明,IIC提高了预测潜力。 这在三个计算实验中确认,随机分裂与甜度相关的数据,进入训练和验证集。

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