Table of Contents Author Guidelines Submit a Manuscript
Comparative and Functional Genomics
Volume 6, Issue 7-8, Pages 373-378
Research article

Using Multiple Ontologies to Integrate Complex Biological Data

1Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee 53226, WI, USA
2Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee 53226, WI, USA

Received 12 September 2005; Revised 17 October 2005; Accepted 7 November 2005

Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease.