A density-based approach for detecting complexes in weighted PPI networks by semantic similarity

作者：Zhou, HongFang^*; Liu, Jie; Li, JunHuai; Duan, WenCong

来源：PLos One, 2017, 12(7): e0180570.

DOI：10.1371/journal.pone.0180570

• OVERLAPPING PROTEIN COMPLEXES
• ALGORITHM
• IDENTIFICATION
• INFORMATION

Protein complex detection in PPI networks plays an important role in analyzing biological processes. A new algorithm-DBGPWN-is proposed for predicting complexes in PPI networks. Firstly, a method based on gene ontology is used to measure semantic similarities between interacted proteins, and the similarity values are used as their weights. Then, a density-based graph partitioning algorithm is developed to find clusters in the weighted PPI networks, and the identified ones are considered to be dense and similar. Experimental results demonstrate that our approach achieves good performance as compared with such algorithms as MCL, CMC, MCODE, RNSC, CORE, ClusterOne and FGN.

• 出版日期2017-7-12
• 单位西安理工大学