title: Mapping plant interactomes using literature curated and predicted protein-protein interaction data sets.
abstract: Most cellular processes are enabled by cohorts of interacting proteins that form dynamic networks within the plant proteome. The study of these networks can provide insight into protein function and provide new avenues for research. This article informs the plant science community of the currently available sources of protein interaction data and discusses how they can be useful to researchers. Using our recently curated IntAct Arabidopsis thaliana protein-protein interaction data set as an example, we discuss potentials and limitations of the plant interactomes generated to date. In addition, we present our efforts to add value to the interaction data by using them to seed a proteome-wide map of predicted protein subcellular locations.
authors.affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon 443-749, Korea. kiylee@ajou.ac.kr
authors.forename: KiYoung
authors.initials: K
authors.lastname: Lee
authors.forename: David
authors.initials: D
authors.lastname: Thorneycroft
authors.forename: Premanand
authors.initials: P
authors.lastname: Achuthan
authors.forename: Henning
authors.initials: H
authors.lastname: Hermjakob
authors.forename: Trey
authors.initials: T
authors.lastname: Ideker
mesh_terms: D017360:Arabidopsis / Q000378:metabolism; D029681:Arabidopsis Proteins / Q000378:metabolism*; D019295:Computational Biology; D030562:Databases, Protein; D025941:Protein Interaction Mapping; D020543:Proteome / Q000378:metabolism
chemical_list: D029681:Arabidopsis Proteins; D020543:Proteome