Abstract
BackgroundThere exist several information resources about orthology of genes and proteins, and there are also systems for querying those resources in an integrated way. However, caveats with current approaches include lack of integration, since results are shown sequentially by resource, meaning that there is redundant information and the users are required to combine the results obtained manually.ResultsIn this paper we have applied the Ontological Gene Orthology approach, which makes use of a domain ontology to integrate the information output from selected orthology resources. The integrated information is stored in a knowledge base, which can be queried through semantic languages. A friendly user interface has been developed to facilitate the search; consequently, users do not need to have knowledge on ontologies or ontological languages to obtain the relevant information.ConclusionThe development and application of our approach allows users to retrieve integrated results when querying orthology information, providing a gene product-oriented output instead of a traditional information resource-oriented one. Besides this benefit for users, it also allows a better exploitation and management of orthology information and knowledge.
Highlights
There exist several information resources about orthology of genes and proteins, and there are systems for querying those resources in an integrated way
That was the origin of the Gene Ontology (GO) [5], which solves the semantic heterogeneity associated to the annotation of gene products between different databases
The Ontological Gene Orthology (OGO) ontology This ontology has been developed to model the knowledge related to orthology and to guide the integration of data by means of mappings between the resources and the concepts of the ontology
Summary
There exist several information resources about orthology of genes and proteins, and there are systems for querying those resources in an integrated way. In order to achieve this goal, the availability of computational methods for organizing, accessing and retrieving information in a systematic way has become crucial, as well as the development of methods that allow the definition and maintenance of shared domain models [1]. There are databases for almost any biological field of study, most of them contain information about genes and proteins from different organisms. New databases were designed to integrate that disperse information in order to provide a common reference for genes and proteins, such as NCBI Entrez [3] or UniProt [4]. The success of GO provoked a huge interest in designing, developing and using biological ontologies, whose number has rapidly increased [7]. Projects such as the OBO Foundry [8] promote the development and use of bio-ontologies
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