Computational Prediction of Protein–Protein Interaction Networks: Algorithms and Resources

Title:Computational Prediction of Protein–Protein Interaction Networks: Algorithms and Resources

Volume: 14 Issue: 6

Author(s): Javad Zahiri, Joseph Hannon Bozorgmehr and Ali Masoudi-Nejad

Affiliation:

Keywords: Protein-protein interaction, Protein interaction networks, Computational prediction method, Machine learning, Networks analyzing tools, Interaction database, Gold standard dataset selection.

Abstract: Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.

Cite this article as:

Zahiri Javad, Bozorgmehr Hannon Joseph and Masoudi-Nejad Ali, Computational Prediction of Protein–Protein Interaction Networks: Algorithms and Resources, Current Genomics 2013; 14 (6) . https://dx.doi.org/10.2174/1389202911314060004