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The Recognition of 27-Class Protein Folds: Approached by Increment of Diversity Based on Multi-Characteristic Parameters

机译:27类蛋白质折叠的识别:基于多特征参数的多样性增加

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摘要

Based on the primary sequence, by selecting the pseudo amino acid composition, position weight matrix score, the predicted secondary structure and the second neighbor dipeptide composition as characteristic parameters, an approach of diversity increment for predicting 27-class protein folds is proposed. Overall recognition accuracy reaches 61.10% in the independent testing.
机译:基于一级序列,通过选择假氨基酸组成,位置权重矩阵评分,预测的二级结构和第二邻二肽组成作为特征参数,提出了一种预测27类蛋白质折叠倍数的多样性增量方法。独立测试的整体识别准确率达到61.10%。

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