EnPC: An Ensemble Clustering Framework for Detecting Protein Complexes in Protein-Protein Interaction Network

Title:EnPC: An Ensemble Clustering Framework for Detecting Protein Complexes in Protein-Protein Interaction Network

Volume: 13 Issue: 2

Author(s): Qiguo Dai, Xiaodong Duan, Maozu Guo and Yingjie Guo

Affiliation:

Keywords: Clustering, ensemble, protein complex, protein-protein interaction.

Abstract: Background: Proteins interact with each other to form a complex, which plays a key role in a cell. Many methods have been proposed to predict complexes by clustering protein-protein interaction networks. However, it remains a challenge to identify protein complexes accurately.

Objective: Although each of previous methods has its advantage in predicting complexes, there is no one method that is always superior to others. Therefore, the goal of this work is propose an ensemble method to integrate the results of multiple previous methods, to obtain a better performance than using a single one of them.

Method: We present an ensemble framework, named EnPC, to combine the results from several existing methods. A cluster- wise voting mechanism is employed to extract the consensus information embedded in the results of different methods. Furthermore, we employ a least squares-based optimization to predict complexes from the matrix.

Results: We test the proposed framework on several widely used yeast PPI networks. The experimental results show that EnPC framework achieves a better performance on detecting protein complexes than other tested base methods.

Conclusion: We conclude that the proposed EnPC framework is suitable to integrate the results of tested base methods for detecting protein complexes from PPI networks.

Cite this article as:

Dai Qiguo, Duan Xiaodong, Guo Maozu and Guo Yingjie, EnPC: An Ensemble Clustering Framework for Detecting Protein Complexes in Protein-Protein Interaction Network, Current Proteomics 2016; 13 (2) . https://dx.doi.org/10.2174/157016461302160514005420