Discovering essential proteins based on PPI network and protein complex

作者：Ren, Jun; Wang, Jianxin^*; Li, Min; Wu, Fangxiang

来源：International Journal of Data Mining and Bioinformatics, 2015, 12(1): 24-43.

DOI：10.1504/IJDMB.2015.068951

• centrality measure
• complex centrality
• essential proteins
• harmonic centrality
• PPI network
• protein complex

Most computational methods for identifying essential proteins focus on the topological centrality of protein-protein interaction (PPI) networks. However, these methods have limitations, such as the difficulty for identifying essential proteins with low centrality values and the poor performance for incomplete PPI network. In this paper, protein complex is proven to be an important factor for determining protein essentiality and a new centrality measure, complex centrality, is proposed. The weighted average of complex centrality and subgraph centrality, called harmonic centrality (HC), is proposed to predict essential proteins. It combines PPI network topology and protein complex information and has better performance than methods based on PPI network. The improvement is higher when the PPI network is incomplete. Furthermore, a weighted PPI network is generated by integrating cellular localisation and biological process to a PPI network. The performance of HC measure is improved 5% in this weighted PPI network.

• 出版日期2015
• 单位湖南农业大学; 中南大学