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Protein three-dimensional structural forecasting manner

机译:蛋白质三维结构预测方法

摘要

PURPOSE:To predict each local structure of the three-dimensional structure of a structure-unknown protein from amino acid sequence information on the protein with high precision. CONSTITUTION:In a step 21, structure-known and structure-unknown protein amino acid sequence are inputted and plus examples of local structure areas are outputted from their alignment (matching). In a step 22, protein amino acid sequence whose three-dimensional structures are already known are inputted and negative examples of local structure areas are outputted from their alignment. In a step 23, the plus examples and negative examples are inputted and estimated values of real numeral parameters of a probable rule are calculated from the amino acid kind or real numeral attributes of training data. In a step 24, the structure of the probable rule representing the dependency relation among variables corresponding to respective residual radical positions is determined on the basis of information amount standards. In a step 25, a test data sequence is inputted and the stochastic rule is used to output activity indicating the probability that the respective areas of the test data sequence are in local structure. In a step 26, activity values are inputted and an optimum value among them is outputted.
机译:目的:从结构蛋白的氨基酸序列信息中高精度预测结构未知蛋白三维结构的每个局部结构。组成:在步骤21中,输入结构已知和结构未知的蛋白质氨基酸序列,并从其比对(匹配)中输出局部结构区域的实例。在步骤22中,输入已经知道其三维结构的蛋白质氨基酸序列,并从其比对输出局部结构区域的阴性实例。在步骤23中,输入正例和负例,并从训练数据的氨基酸种类或实数属性计算出可能规则的实数参数的估计值。在步骤24中,基于信息量标准,确定表示对应于各个剩余部首位置的变量之间的依赖关系的可能性规则的结构。在步骤25中,输入测试数据序列,并且使用随机规则来输出活动,该活动指示测试数据序列的各个区域处于局部结构中的概率。在步骤26中,输入活动值并输出其中的最优值。

著录项

  • 公开/公告号JP3012441B2

    专利类型

  • 公开/公告日2000-02-21

    原文格式PDF

  • 申请/专利权人 日本電気株式会社;

    申请/专利号JP19930246805

  • 发明设计人 馬見塚 拓;

    申请日1993-10-01

  • 分类号G06F17/00;G06F17/30;

  • 国家 JP

  • 入库时间 2022-08-22 02:04:12

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