Motivation: 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.
Bibliographical noteFunding Information:
We thank Michael Lachmann, Katrin Loebe, and Kay Prüfer for helpful discussions and critical reading of the manuscript. We thank the Max Planck Society, the German Federal Ministry of Education and Research, the Institute of Medical Informatics, Statistics and Epidemiology, and the Graduiertenkolleg Knowledge Representation of the German Research Foundation for financial support.
ASJC Scopus subject areas
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics