Abstract
BackgroundIntegration and exploration of data obtained from genome wide monitoring technologies has become a major challenge for many bioinformaticists and biologists due to its heterogeneity and high dimensionality. A widely accepted approach to solve these issues has been the creation and use of controlled vocabularies (ontologies). Ontologies allow for the formalization of domain knowledge, which in turn enables generalization in the creation of querying interfaces as well as in the integration of heterogeneous data, providing both human and machine readable interfaces.ResultsWe designed and implemented a software tool that allows investigators to create their own semantic model of an organism and to use it to dynamically integrate expression data obtained from DNA microarrays and other probe based technologies. The software provides tools to use the semantic model to postulate and validate of hypotheses on the spatial and temporal expression and function of genes. In order to illustrate the software's use and features, we used it to build a semantic model of rice (Oryza sativa) and integrated experimental data into it.ConclusionIn this paper we describe the development and features of a flexible software application for dynamic gene expression data annotation, integration, and exploration called Orymold. Orymold is freely available for non-commercial users from
Highlights
Integration and exploration of data obtained from genome wide monitoring technologies has become a major challenge for many bioinformaticists and biologists due to its heterogeneity and high dimensionality
BMC Bioinformatics 2009, 10:158 http://www.biomedcentral.com/1471-2105/10/158 faces and integration of data has been the development of controlled vocabularies [4,5]
Ontology construction has been a hot topic for several years in the bioinformatics field since it provides a rich framework for dynamic annotation, sharing of data, and formalization of domain knowledge
Summary
Integration and exploration of data obtained from genome wide monitoring technologies has become a major challenge for many bioinformaticists and biologists due to its heterogeneity and high dimensionality. A widely accepted approach to solve these issues has been the creation and use of controlled vocabularies (ontologies). Ontologies allow for the formalization of domain knowledge, which in turn enables generalization in the creation of querying interfaces as well as in the integration of heterogeneous data, providing both human and machine readable interfaces. The availability of genome and proteome wide expression monitoring techniques such as DNA microarrays (MA), and established molecular biology techniques like in situ hybridization (ISH) are crucial in the understanding of the genetic complexity of organisms. BMC Bioinformatics 2009, 10:158 http://www.biomedcentral.com/1471-2105/10/158 faces and integration of data has been the development of controlled vocabularies (ontologies) [4,5]. Ontology properties promote the creation of comprehensive views and comparisons of data both on a human and machine comprehensive basis
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