Using multiple ontologies to integrate complex biological data

Mary Shimoyama,Susan Bromberg,Nataliya Nenasheva,Simon Twigger,Jiali Chen,Wenhua Wu,Dean Pasko,Victoria Petri,Anne Kwitek,Howard Jacob

doi:10.1002/cfg.498

Mary Shimoyama, Susan Bromberg + Show 8 more

Open Access

https://doi.org/10.1002/cfg.498

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Abstract

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.

Highlights

The Rat Genome Database (RGD) used ontologies to provide a simple framework for classifying, representing and navigating across gene, phenotype and disease information to link genomic data to function and disease (Ashburner and Lewis, 2002; Stevens et al, 2000) and as a means of providing a view of biological information in the context of the genome
The disease ontology was adapted from the Medical Subject Headings (MeSH; Nelson et al, 2001) and the pathway ontology was developed at RGD in order to integrate data from existing pathway databases, such as the Kyoto Encyclopedia of Genes and Genomes (Kanehisa, 2002), REACTOME (Joshi-Tope et al, 2005), GenMapDB (Dahlquist et al, 2002) and the Biomolecular Interaction Database (Bader et al, 2003), as well as pathway data found in the literature
Because the rat is used by a diverse community involved in physiological and disease research, investigators are often unsure of the best model to use to study particular phenotypes

Summary

Introduction

The Rat Genome Database (RGD) used ontologies to provide a simple framework for classifying, representing and navigating across gene, phenotype and disease information to link genomic data to function and disease (Ashburner and Lewis, 2002; Stevens et al, 2000) and as a means of providing a view of biological information in the context of the genome. RGD developed a structure that would allow the integration of multiple ontology annotations, as well as qualifiers and actual values, into a single record.

Results

Conclusion