Chen Yu, Wang Wei, Liu Jiale, Feng Jinping, Gong Xinqi
School of Mathematics, Renmin University of China, Beijing, China.
School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, China.
Front Genet. 2020 Apr 2;11:291. doi: 10.3389/fgene.2020.00291. eCollection 2020.
Protein-protein interactions are the foundations of cellular life activities. At present, the already known protein-protein interactions only account for a small part of the total. With the development of experimental and computing technology, more and more PPI data are mined, PPI networks are more and more dense. It is possible to predict protein-protein interaction from the perspective of network structure. Although there are many high-throughput experimental methods to detect protein-protein interactions, the cost of experiments is high, time-consuming, and there is a certain error rate meanwhile. Network-based approaches can provide candidates of protein pairs for high-throughput experiments and improve the accuracy rate. This paper presents a new link prediction approach "Sim" for PPI networks from the perspectives of proteins' complementary interfaces and gene duplication. By integrating our approach "Sim" with the state-of-art network-based approach "3," the prediction accuracy and robustness are improved.
蛋白质-蛋白质相互作用是细胞生命活动的基础。目前，已知的蛋白质-蛋白质相互作用仅占总数的一小部分。随着实验和计算技术的发展，越来越多的蛋白质-蛋白质相互作用数据被挖掘出来，蛋白质-蛋白质相互作用网络越来越密集。从网络结构的角度预测蛋白质-蛋白质相互作用成为可能。虽然有许多高通量实验方法来检测蛋白质-蛋白质相互作用，但实验成本高、耗时，同时还存在一定的错误率。基于网络的方法可以为高通量实验提供蛋白质对的候选对象，并提高准确率。本文从蛋白质的互补界面和基因复制的角度，提出了一种新的用于蛋白质-蛋白质相互作用网络的链接预测方法“Sim”。通过将我们的方法“Sim”与当前最先进的基于网络的方法“3”相结合，提高了预测的准确性和稳健性。
