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Nucleic Acids Research 2005 33(13):4164-4171; doi:10.1093/nar/gki735
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Published online 25 July 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
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{at}oupjournals.org

Article

MAO: a Multiple Alignment Ontology for nucleic acid and protein sequences

Julie D. Thompson*, Stephen R. Holbrook1, Kazutaka Katoh2, Patrice Koehl3, Dino Moras, Eric Westhof4 and Olivier Poch

Institut de Génétique et deBiologie Moléculaire et Cellulaire 1 rue Laurent Fries, B.P. 10142, 67404 Illkirch Cedex, France 1Lawrence Berkeley National Laboratory 1 Cyclotron Road, Berkeley CA 94720, USA 2Bioinformatics Center, Institute for Chemical Research, Kyoto University Uji, Kyoto 611-0011, Japan 3University of California Davis, One Shields Avenue, Davis CA 95616, USA 4Institut de Biologie Moléculaire et Cellulaire 15, rue René Descartes 67084 Strasbourg Cedex, France

*To whom correspondence should be addressed. Tel: +33 388 65 32 00; Fax: +33 388 65 32 01; Email: julie{at}igbmc.u-strasbg.fr

Received June 9, 2005. Revised July 8, 2005. Accepted July 8, 2005.

The application of high-throughput techniques such as genomics, proteomics or transcriptomics means that vast amounts of heterogeneous data are now available in the public databases. Bioinformatics is responding to the challenge with new integrated management systems for data collection, validation and analysis. Multiple alignments of genomic and protein sequences provide an ideal environment for the integration of this mass of information. In the context of the sequence family, structural and functional data can be evaluated and propagated from known to unknown sequences. However, effective integration is being hindered by syntactic and semantic differences between the different data resources and the alignment techniques employed. One solution to this problem is the development of an ontology that systematically defines the terms used in a specific domain. Ontologies are used to share data from different resources, to automatically analyse information and to represent domain knowledge for non-experts. Here, we present MAO, a new ontology for multiple alignments of nucleic and protein sequences. MAO is designed to improve interoperation and data sharing between different alignment protocols for the construction of a high quality, reliable multiple alignment in order to facilitate knowledge extraction and the presentation of the most pertinent information to the biologist.


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