Journal
BMC BIOINFORMATICS
Volume 15, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12859-014-0383-1
Keywords
Protein-protein interactions; Computational prediction; Human proteome; Massively parallel computing; Personalized medicine; Interactome; Network analysis
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Funding
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Canadian Institutes of Health Research and Saskatchewan Health Research Foundation [RSN-124512]
- European Community Seventh Framework Programme [223367]
- Swedish Research Council, Linkoping University, Sahlgrenska Academy, NIH [R01-AA-018776, 3P20MD000516-07S1]
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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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