A top-level ontology of functions and its application in the Open Biomedical Ontologies.
BACKGROUND
A clear understanding of functions in biology is a key component in accurate modelling of molecular, cellular and organismal biology. Using the existing biomedical ontologies it has been impossible to capture the complexity of the community's knowledge about biological functions.


RESULTS
We present here a top-level ontological framework for representing knowledge about biological functions. This framework lends greater accuracy, power and expressiveness to biomedical ontologies by providing a means to capture existing functional knowledge in a more formal manner. An initial major application of the ontology of functions is the provision of a principled way in which to curate functional knowledge and annotations in biomedical ontologies. Further potential applications include the facilitation of ontology interoperability and automated reasoning. A major advantage of the proposed implementation is that it is an extension to existing biomedical ontologies, and can be applied without substantial changes to these domain ontologies.


BACKGROUND
The Ontology of Functions (OF) can be downloaded in OWL format from http://onto.eva.mpg.de/. Additionally, a UML profile and supplementary information and guides for using the OF can be accessed from the same website.
Burek
Patryk
P
Department of Computer Science, Faculty of Mathematics and Computer Science, University of Leipzig, Augustusplatz 10-11, 04109 Leipzig.
Hoehndorf
Robert
R
Loebe
Frank
F
Visagie
Johann
J
Herre
Heinrich
H
Kelso
Janet
J
D001698:Biomedical Engineering / Q000379:methods; D019295:Computational Biology / Q000379:methods; D003628:Database Management Systems; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D009323:Natural Language Processing; D011506:Proteins / Q000737:chemistry / Q000145:classification* / Q000378:metabolism*; D013329:Structure-Activity Relationship
D011506:Proteins