title: Protein function prediction--the power of multiplicity.
abstract: Advances in experimental and computational methods have quietly ushered in a new era in protein function annotation. This 'age of multiplicity' is marked by the notion that only the use of multiple tools, multiple evidence and considering the multiple aspects of function can give us the broad picture that 21st century biology will need to link and alter micro- and macroscopic phenotypes. It might also help us to undo past mistakes by removing errors from our databases and prevent us from producing more. On the downside, multiplicity is often confusing. We therefore systematically review methods and resources for automated protein function prediction, looking at individual (biochemical) and contextual (network) functions, respectively.
authors.affiliation: Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK. rentzsch@biochem.ucl.ac.uk
authors.forename: Robert
authors.initials: R
authors.lastname: Rentzsch
authors.forename: Christine A
authors.initials: CA
authors.lastname: Orengo
mesh_terms: D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D010363:Pattern Recognition, Automated; D010802:Phylogeny; D011506:Proteins / Q000737:chemistry / Q000502:physiology*
chemical_list: D011506:Proteins