Lee Anthony J T, Lin Ming-Chih, Hsu Chia-Ming
Department of Information Management, National Taiwan University, Taipei, Taiwan, ROC.
Biosystems. 2011 Mar;103(3):392-9. doi: 10.1016/j.biosystems.2010.11.010. Epub 2010 Nov 21.
Many methods have been proposed for mining protein complexes from a protein-protein interaction network; however, most of them focus on unweighted networks and cannot find overlapping protein complexes. Since one protein may serve different roles within different functional groups, mining overlapping protein complexes in a weighted protein-protein interaction network has attracted more and more attention recently. In this paper, we propose an effective method, called MDOS (Mining Dense Overlapping Subgraphs), for mining dense overlapping protein complexes (subgraphs) in a weighted protein-protein interaction network. The proposed method can integrate the information about known complexes into a weighted protein-protein interaction network to improve the mining results. The experiment results show that our method mines more known complexes and has higher sensitivity and accuracy than the CODENSE and MCL methods.
已经提出了许多从蛋白质 - 蛋白质相互作用网络中挖掘蛋白质复合物的方法；然而，它们中的大多数都集中在无权网络上，无法找到重叠的蛋白质复合物。由于一个蛋白质可能在不同的功能组中发挥不同的作用，因此在加权蛋白质 - 蛋白质相互作用网络中挖掘重叠蛋白质复合物最近受到了越来越多的关注。在本文中，我们提出了一种有效的方法，称为MDOS（挖掘密集重叠子图），用于在加权蛋白质 - 蛋白质相互作用网络中挖掘密集重叠的蛋白质复合物（子图）。所提出的方法可以将关于已知复合物的信息整合到加权蛋白质 - 蛋白质相互作用网络中，以改善挖掘结果。实验结果表明，我们的方法挖掘出了更多已知复合物，并且比CODENSE和MCL方法具有更高的灵敏度和准确性。
