title: Combining many interaction networks to predict gene function and analyze gene lists.
abstract: In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems.
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA, USA.
authors.forename: Sara
authors.initials: S
authors.lastname: Mostafavi
authors.forename: Quaid
authors.initials: Q
authors.lastname: Morris
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005796:Genes / Q000502:physiology*; D006801:Humans; D020407:Internet; D051379:Mice; D025941:Protein Interaction Mapping / Q000379:methods; D011506:Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism
chemical_list: D011506:Proteins