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.

Additional Metadata
Keywords Computational prediction, Human proteome, Interactome, Massively parallel computing, Network analysis, Personalized medicine, Protein-protein interactions
Persistent URL dx.doi.org/10.1186/s12859-014-0383-1
Journal BMC Bioinformatics
Citation
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