Abstract
BackgroundWith the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework.In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data.MethodsA version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest.Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite.ResultsWe have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application.ConclusionsThis has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development.The publication of variation information as Linked Data opens new perspectives: the exploitation of SPARQL searches on mutation data and other biological databases may support data retrieval which is presently not possible. Moreover, reasoning on integrated variation data may support discoveries towards personalized medicine.
Highlights
With the advent of high-throughput technologies, a great wealth of variation data is being produced
We present the development of a mapping between a relational version of the International Agency for Research on Cancer (IARC) TP53 Mutation database (IARCDB) to Resource Description Framework (RDF) that takes into account Human Genome Variation Society (HGVS) recommendations as well as existing ontologies for the representation of this domain knowledge
A prototype implementation We have implemented a D2RQ Server for TP53 mutation data as a prototype for studying issues related to the publication of mutation data on the Linked Open Data (LOD) framework
Summary
With the advent of high-throughput technologies, a great wealth of variation data is being produced. The vision of the Semantic Web is to evolve the Web into a distributed knowledge base: this vision relies on its evolution from the current Web of Documents, where each node of the network is represented by an unstructured document, into a Web of Data, where each node represents machine processable information. In this context, access to information is achieved through portals and search engines whose behavior is supported by semantic features. Semantics can be associated to property definitions, while subjects usually are well identified entities and objects may either represent related entities or values
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