title: Computational methods for predicting protein-protein interactions.
abstract: Protein-protein interactions (PPIs) play a critical role in many cellular functions. A number of experimental techniques have been applied to discover PPIs; however, these techniques are expensive in terms of time, money, and expertise. There are also large discrepancies between the PPI data collected by the same or different techniques in the same organism. We therefore turn to computational techniques for the prediction of PPIs. Computational techniques have been applied to the collection, indexing, validation, analysis, and extrapolation of PPI data. This chapter will focus on computational prediction of PPI, reviewing a number of techniques including PIPE, developed in our own laboratory. For comparison, the conventional large-scale approaches to predict PPIs are also briefly discussed. The chapter concludes with a discussion of the limitations of both experimental and computational methods of determining PPIs.
authors.affiliation: School of Computer Science, Carleton University, 5304 Herzberg Building, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, Canada.
authors.forename: Sylvain
authors.initials: S
authors.lastname: Pitre
authors.forename: Md
authors.initials: M
authors.lastname: Alamgir
authors.forename: James R
authors.initials: JR
authors.lastname: Green
authors.forename: Michel
authors.initials: M
authors.lastname: Dumontier
authors.forename: Frank
authors.initials: F
authors.lastname: Dehne
authors.forename: Ashkan
authors.initials: A
authors.lastname: Golshani
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*
chemical_list: D020543:Proteome