Background: Proteins and their interactions are fundamental to biological systems and they are affecting our body. Functional study of protein networks is becoming increasingly essential to get a deep understanding of proteins and their roles in human life and diseases. Although several methods already exist for protein-protein interaction (PPI) network building, the precise reconstruction of disease associated PPI network remains a challenge. In this paper we introduce a novel concept of comprehensive influence of proteins in network, in which direct and indirect connections are adopted for the calculation of influential effects of a protein with different weights. With the optimized weights, we calculate and select the important proteins and their interactions to reconstruct the PPI network for further validation and confirmation.
Results: To evaluate the performance of the method, we compared our model with six existing methods using five standard data sets.
Conclusions: The results indicated that our method outperforms the existed ones. We then applied our model to prostate cancer and Parkinson’s disease to predict novel disease associated proteins for the future experimental validation.