title: An innovative portal for rare genetic diseases research: the semantic Diseasecard.
abstract: Advances in "omics" hardware and software technologies are bringing rare diseases research back from the sidelines. Whereas in the past these disorders were seldom considered relevant, in the era of whole genome sequencing the direct connections between rare phenotypes and a reduced set of genes are of vital relevance. This increased interest in rare genetic diseases research is pushing forward investment and effort towards the creation of software in the field, and leveraging the wealth of available life sciences data. Alas, most of these tools target one or more rare diseases, are focused solely on a single type of user, or are limited to the most relevant scientific breakthroughs for a specific niche. Furthermore, despite some high quality efforts, the ever-growing number of resources, databases, services and applications is still a burden to this area. Hence, there is a clear interest in new strategies to deliver a holistic perspective over the entire rare genetic diseases research domain. This is Diseasecard's reasoning, to build a true lightweight knowledge base covering rare genetic diseases. Developed with the latest semantic web technologies, this portal delivers unified access to a comprehensive network for researchers, clinicians, patients and bioinformatics developers. With in-context access covering over 20 distinct heterogeneous resources, Diseasecard's workspace provides access to the most relevant scientific knowledge regarding a given disorder, whether through direct common identifiers or through full-text search over all connected resources. In addition to its user-oriented features, Diseasecard's semantic knowledge base is also available for direct querying, enabling everyone to include rare genetic diseases knowledge in new or existing information systems. Diseasecard is publicly available at http://bioinformatics.ua.pt/diseasecard/.
authors: DETI/IEETA, Universidade de Aveiro, Portugal. Electronic address: pedrolopes@ua.pt.
authors: Pedro
authors: P
authors: Lopes
authors: José Luís
authors: JL
authors: Oliveira
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D035583:Rare Diseases / Q000235:genetics*; D012984:Software
keywords: Biomedical semantics; Data integration; Interoperability; Rare diseases; Semantic web