Journal
BMC BIOINFORMATICS
Volume 15, Issue -, Pages -Publisher
BMC
DOI: 10.1186/1471-2105-15-335
Keywords
Dynamic protein-protein interaction; Gene expression; Stable interaction; Transient interaction; Protein complex
Categories
Funding
- National Science Foundation of China [11171354, 61375033, 61402190]
- Ministry of Education of China [20120171110016]
- Natural Science Foundation of Guangdong Province [S2013020012796]
- International Program Fund of 985 Project, Sun Yat-sen University
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Background: Proteins dynamically interact with each other to perform their biological functions. The dynamic operations of protein interaction networks (PPI) are also reflected in the dynamic formations of protein complexes. Existing protein complex detection algorithms usually overlook the inherent temporal nature of protein interactions within PPI networks. Systematically analyzing the temporal protein complexes can not only improve the accuracy of protein complex detection, but also strengthen our biological knowledge on the dynamic protein assembly processes for cellular organization. Results: In this study, we propose a novel computational method to predict temporal protein complexes. Particularly, we first construct a series of dynamic PPI networks by joint analysis of time-course gene expression data and protein interaction data. Then a Time Smooth Overlapping Complex Detection model (TS-OCD) has been proposed to detect temporal protein complexes from these dynamic PPI networks. TS-OCD can naturally capture the smoothness of networks between consecutive time points and detect overlapping protein complexes at each time point. Finally, a nonnegative matrix factorization based algorithm is introduced to merge those very similar temporal complexes across different time points. Conclusions: Extensive experimental results demonstrate the proposed method is very effective in detecting temporal protein complexes than the state-of-the-art complex detection techniques.
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