Predicting overlapping protein complexes based on core-attachment and a local modularity structure.

ABSTRACT:

Background

In recent decades, detecting protein complexes (PCs) from protein-protein interaction networks (PPINs) has been an active area of research. There are a large number of excellent graph clustering methods that work very well for identifying PCs. However, most of existing methods usually overlook the inherent core-attachment organization of PCs. Therefore, these methods have three major limitations we should concern. Firstly, many methods have ignored the importance of selecting seed, especially without considering the impact of overlapping nodes as seed nodes. Thus, there may be false predictions. Secondly, PCs are generally supposed to be dense subgraphs. However, the subgraphs with high local modularity structure usually correspond to PCs. Thirdly, a number of available

SUBMITTER: Wang R 

PROVIDER: S-EPMC6106838 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature