Background: Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. Results: On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. Conclusions: The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

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Keywords Computational prediction, Human proteome, Interactome, Massively parallel computing, Network analysis, Personalized medicine, Protein-protein interactions
Persistent URL
Journal BMC Bioinformatics
Schoenrock, A. (Andrew), Samanfar, B. (Bahram), Pitre, S, Hooshyar, M. (Mohsen), Jin, K. (Ke), Phillips, C.A. (Charles A.), … Golshani, A. (2014). Efficient prediction of human protein-protein interactions at a global scale. BMC Bioinformatics, 15(1). doi:10.1186/s12859-014-0383-1