title: Systematic computational prediction of protein interaction networks.
abstract: Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use.
authors.affiliation: Research Department of Structural & Molecular Biology, University College London, London, UK. lees@biochem.ucl.ac.uk
authors.forename: J G
authors.initials: JG
authors.lastname: Lees
authors.forename: J K
authors.initials: JK
authors.lastname: Heriche
authors.forename: I
authors.initials: I
authors.lastname: Morilla
authors.forename: J A
authors.initials: JA
authors.lastname: Ranea
authors.forename: C A
authors.initials: CA
authors.lastname: Orengo
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008958:Models, Molecular; D011487:Protein Conformation; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D011506:Proteins