SIAT, Chinese Academy of Sciences
A Semi-Supervised Network Embedding Model for Protein Complexes Detection
Zhao, Wei (SIAT, Chinese Academy of Sciences) | Zhu, Jia (South China Normal University) | Yang, Min (SIAT, Chinese Academy of Sciences) | Xiao, Danyang (South China Normal University) | Fung, Gabriel Pui Cheong (The Chinese University of Hong Kong) | Chen, Xiaojun (Shenzhen University)
Protein complex is a group of associated polypeptide chains which plays essential roles in biological process. Given a graph representing protein-protein interactions (PPI) network, it is critical but non-trivial to detect protein complexes.In this paper, we propose a semi-supervised network embedding model by adopting graph convolutional networks to effectively detect densely connected subgraphs. We conduct extensive experiment on two popular PPI networks with various data sizes and densities. The experimental results show our approach achieves state-of-the-art performance.