title: Ontology-based knowledge representation for bioinformatics.
abstract: Much of biology works by applying prior knowledge ('what is known') to an unknown entity, rather than the application of a set of axioms that will elicit knowledge. In addition, the complex biological data stored in bioinformatics databases often require the addition of knowledge to specify and constrain the values held in that database. One way of capturing knowledge within bioinformatics applications and databases is the use of ontologies. An ontology is the concrete form of a conceptualisation of a community's knowledge of a domain. This paper aims to introduce the reader to the use of ontologies within bioinformatics. A description of the type of knowledge held in an ontology will be given.The paper will be illustrated throughout with examples taken from bioinformatics and molecular biology, and a survey of current biological ontologies will be presented. From this it will be seen that the use to which the ontology is put largely determines the content of the ontology. Finally, the paper will describe the process of building an ontology, introducing the reader to the techniques and methods currently in use and the open research questions in ontology development.
authors.affiliation: Department of Computer Science, University of Manchester, UK. robert.stevens@cs.man.ac.uk
authors.forename: R
authors.initials: R
authors.lastname: Stevens
authors.forename: C A
authors.initials: CA
authors.lastname: Goble
authors.forename: S
authors.initials: S
authors.lastname: Bechhofer
mesh_terms: D001185:Artificial Intelligence; D002965:Classification; D019295:Computational Biology; D016208:Databases, Factual; D015509:Developmental Biology / Q000706:statistics & numerical data; D008967:Molecular Biology / Q000706:statistics & numerical data; D012984:Software