title: Automatic assignment of EC numbers.
abstract: A wide range of research areas in molecular biology and medical biochemistry require a reliable enzyme classification system, e.g., drug design, metabolic network reconstruction and system biology. When research scientists in the above mentioned areas wish to unambiguously refer to an enzyme and its function, the EC number introduced by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (IUBMB) is used. However, each and every one of these applications is critically dependent upon the consistency and reliability of the underlying data for success. We have developed tools for the validation of the EC number classification scheme. In this paper, we present validated data of 3788 enzymatic reactions including 229 sub-subclasses of the EC classification system. Over 80% agreement was found between our assignment and the EC classification. For 61 (i.e., only 2.5%) reactions we found that their assignment was inconsistent with the rules of the nomenclature committee; they have to be transferred to other sub-subclasses. We demonstrate that our validation results can be used to initiate corrections and improvements to the EC number classification scheme.
authors.affiliation: Department of Bioinformatics and Biochemistry, Technical University Braunschweig, Braunschweig, Germany. volker.egelhofer@univie.ac.at
authors.forename: Volker
authors.initials: V
authors.lastname: Egelhofer
authors.forename: Ida
authors.initials: I
authors.lastname: Schomburg
authors.forename: Dietmar
authors.initials: D
authors.lastname: Schomburg
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D004798:Enzymes / Q000737:chemistry / Q000145:classification; D015203:Reproducibility of Results
chemical_list: D004798:Enzymes