Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions
Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions
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DOI：
10.1093/bioinformatics/btl419
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发表时间：
2006-10-15
期刊：
影响因子：
5.8
通讯作者：
Toh, Hiroyuki
中科院分区：
文献类型：
--
作者：
Sato, Tetsuya;Yamanishi, Yoshihiro;Toh, Hiroyuki
动机：蛋白质相互作用的计算预测是目前生物信息学中的一个主要问题。最近，各种基于协同进化的方法已经朝着这个目标进行了研究。在这项研究中，我们引入了偏相关系数作为一个新的措施，蛋白质之间的协同进化的程度，并提出了使用它来预测蛋白质-蛋白质interactions.Results：预测的准确性由所提出的方法进行了比较，与原来的镜像树方法和投影方法先前开发的我们的小组。我们发现，偏相关系数有效地减少了假阳性的数量，与其他方法相比，虽然假阴性的数量增加了预测的偏相关系数。
Motivation: The computational prediction of protein-protein interactions is currently a major issue in bioinformatics. Recently, a variety of co-evolution-based methods have been investigated toward this goal. In this study, we introduced a partial correlation coefficient as a new measure for the degree of co-evolution between proteins, and proposed its use to predict protein-protein interactions.Results: The accuracy of the prediction by the proposed method was compared with those of the original mirror tree method and the projection method previously developed by our group. We found that the partial correlation coefficient effectively reduces the number of false positives, as compared with other methods, although the number of false negatives increased in the prediction by the partial correlation coefficient.