title: Network-based prediction of protein function.
abstract: Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function. In this review, we describe the current computational approaches for the task, including direct methods, which propagate functional information through the network, and module-assisted methods, which infer functional modules within the network and use those for the annotation task. Although a broad variety of interesting approaches has been developed, further progress in the field will depend on systematic evaluation of the methods and their dissemination in the biological community.
authors.affiliation: School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Roded
authors.initials: R
authors.lastname: Sharan
authors.forename: Igor
authors.initials: I
authors.lastname: Ulitsky
authors.forename: Ron
authors.initials: R
authors.lastname: Shamir
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D007255:Information Services; D008962:Models, Theoretical; D011506:Proteins / Q000502:physiology*
chemical_list: D011506:Proteins