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Bioinformatics 2006 22(14):e530-e538; doi:10.1093/bioinformatics/btl208
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Protein classification using ontology classification

K. Wolstencroft 1,2,*, P. Lord 1,#, L. Tabernero 2, A. Brass 1,2 and R. Stevens 1

1 School of Computer Science, University of Manchester UK
2 Faculty of Life Sciences, University of Manchester UK

*To whom correspondence should be addressed.

Motivation: The classification of proteins expressed by an organism is an important step in understanding the molecular biology of that organism. Traditionally, this classification has been performed by human experts. Human knowledge can recognise the functional properties that are sufficient to place an individual gene product into a particular protein family group. Automation of this task usually fails to meet the ‘gold standard’ of the human annotator because of the difficult recognition stage. The growing number of genomes, the rapid changes in knowledge and the central role of classification in the annotation process, however, motivates the need to automate this process.

Results: We capture human understanding of how to recognise members of the protein phosphatases family by domain architecture as an ontology. By describing protein instances in terms of the domains they contain, it is possible to use description logic reasoners and our ontology to assign those proteins to a protein family class.

We have tested our system on classifying the protein phosphatases of the human and Aspergillus fumigatus genomes and found that our knowledge-based, automatic classification matches, and sometimes surpasses, that of the human annotators. We have made the classification process fast and reproducible and, where appropriate knowledge is available, the method can potentially be generalised for use with any protein family.

Availability: All components described in this paper are freely available.

OWL ontology http://www.bioinf.man.ac.uk/phosphabase

myGrid http://www.mygrid.org.uk

Instance Store http://instancestore.man.ac.uk

Contact: KWolstencroft{at}cs.man.ac.uk


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