基于概率神经网络的蛋白质相互作用分类器Predicting type of protein-protein interaction based on probabilistic neural network
张伟;郝江锋;项俊平;胡茂林;
摘要(Abstract)：
蛋白质-蛋白质作用面上的结构特征对于研究蛋白质功能具有重要意义。提出了一种新的、基于统计直方图提取蛋白质作用面特征的方法,并且利用提取出的作用面特征,结合概率神经网络,实现了对作用面结构类型的分类预测。从预测结果来看,统计直方图提取出的特征,对蛋白质作用面结构具有很好的区分能力,而且可以通过调节划分的区间个数和节点的选取方式,达到对作用面结构的不同粒度的描述,以适用于不同目的的研究,这可能对与结构有关的某些生物信息学问题的研究具有启发性。利用概率神经网络对作用面结构进行分类预测,避开了费时的结构比对和数据库搜索,且训练快速,扩展能力强,正确率高,对独立测试集的911个蛋白复合物视在正确率达到90.67%。基于该算法的MATLAB分类器软件可以通过E-Mail与作者联系获取。
关键词(KeyWords)： 统计直方图;蛋白质作用面;概率神经网络;结构比对;分类器
基金项目(Foundation):
作者(Author): 张伟;郝江锋;项俊平;胡茂林;
Email:
DOI:
参考文献(References)：
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