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Open Access Correspondence

Muscle Research and Gene Ontology: New standards for improved data integration

Erika Feltrin1*, Stefano Campanaro2, Alexander D Diehl3, Elisabeth Ehler4, Georgine Faulkner5, Jennifer Fordham4, Chiara Gardin1, Midori Harris6, David Hill3, Ralph Knoell7, Paolo Laveder2, Lorenza Mittempergher1, Alessandra Nori8, Carlo Reggiani9, Vincenzo Sorrentino10, Pompeo Volpe8, Ivano Zara1, Giorgio Valle1 and Jennifer Deegan née Clark6

Author Affiliations

1 CRIBI- Interdepartmental Biotechnology Center, University of Padua, Padua, Italy

2 Department of Biology, University of Padua, Padua, Italy

3 The Jackson Laboratory, Bar Harbor, ME, USA

4 Randall Division of Cell & Molecular Biophysics, King's College, London, UK

5 ICGEB, Trieste, Italy

6 EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK

7 Heart Center, Georg August University, Goettingen, Germany

8 Department of Experimental Biomedical Sciences, University of Padua, Padua, Italy

9 Department of Anatomy and Physiology, University of Padua, Padua, Italy

10 Department of Neuroscience, University of Siena, Siena, Italy

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BMC Medical Genomics 2009, 2:6  doi:10.1186/1755-8794-2-6

Published: 29 January 2009

Abstract

Background

The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO) Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community.

Results

The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature.

Conclusion

The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic) experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology webcite.