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Identification of Hot Regions in Protein-Protein Interactions Based on Detecting Local Community Structure

机译:基于检测局部群落结构的蛋白质-蛋白质相互作用中热点区域的鉴定

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Hot regions can help proteins to exert their biological function and contribute to understand the molecular mechanism, which is the foundation of drug designs. In this paper, combining protein biological characteristics, a new method is proposed to predict protein hot regions. Firstly, we used support vector machine to predict the hot spots. Then, the local community structure detecting algorithm based on the identification of boundary nodes was proposed to predict the hot regions in protein-protein interactions. The experimental results demonstrate that the proposed method improves significantly the predictive accuracy and performance of protein hot regions.
机译:高温区域可以帮助蛋白质发挥其生物学功能并有助于理解分子机制,这是药物设计的基础。本文结合蛋白质的生物学特性,提出了一种预测蛋白质热点区域的新方法。首先,我们使用支持向量机来预测热点。然后,提出了基于边界节点识别的局部群落结构检测算法,以预测蛋白质相互作用中的热点区域。实验结果表明,所提出的方法显着提高了蛋白质热点区域的预测准确性和性能。

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