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中文摘要：
基于蛋白质相互作用能量热点的特性，定义了残基接触数、溶剂可及性面积相对变化量所占比例等18个新特征。分别使用基于支持向量机（support vector machine，SVM）和基于 F - Score 的递归特征消除法进行特征选择，提出对应的预测模型 SVM - RFE 和 F - Score - RFE 用于蛋白质能量热点的预测。实验结果显示，在独立测试中 F - Score - RFE 模型的 F1比当前预测性能最好的方法提高6.25％，表明所定义的新特征对蛋白质能量热点的识别具有较大的贡献。
英文摘要：
18 new features such as residue contact number and the proportion of relative change of accessible surface area et al. were derived based on the analysis of protein-protein interaction energy hot spots. Two recursion feature elimina-tion methods were used to select discriminative feature subsets and two corresponding prediction models were proposed, noted as SVM - RFE and F - Score - RFE. The experimental results showed that the prediction model F - Score - RFE could improve 6. 25% in the value of F1 compared with the best existing method on the same independent test dataset, which indicated that new features defined were significant to improve the performance of prediction.
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