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Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.
Sernadela, Pedro; González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Posada, Manuel; Taruscio, Domenica; Lochmüller, Hanns; Robinson, Peter; Roos, Marco; Oliveira, José Luís.
Afiliação
  • Sernadela P; University of Aveiro, DETI/IEETA, Aveiro, Portugal.
  • González-Castro L; Galician Research and Development Center in Advanced Telecommunications (GRADIANT), Pontevedra, Spain.
  • Carta C; National Center for Rare Diseases, Istituto Superiore di Sanità, Rome, Italy.
  • van der Horst E; Leiden University Medical Centre (LUMC), Leiden, Netherlands.
  • Lopes P; University of Aveiro, DETI/IEETA, Aveiro, Portugal.
  • Kaliyaperumal R; Leiden University Medical Centre (LUMC), Leiden, Netherlands.
  • Thompson M; Leiden University Medical Centre (LUMC), Leiden, Netherlands.
  • Thompson R; International Centre for Life, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
  • Queralt-Rosinach N; Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Universitat Pompeu Fabra (UPF), Barcelona, Spain.
  • Lopez E; Institute of Rare Diseases Research, ISCIII, SpainRDR and CIBERER, Madrid, Spain.
  • Wood L; John Walton Muscular Dystrophy Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
  • Robertson A; John Walton Muscular Dystrophy Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
  • Lamanna C; The European Huntington's Disease Network, University Hospital of Ulm, Ulm, Germany.
  • Gilling M; The European Huntington's Disease Network, University Hospital of Ulm, Ulm, Germany.
  • Orth M; Department of Neurology, University Hospital of Ulm, Ulm, Germany.
  • Merino-Martinez R; Karolinska Institutet, Solna, Sweden.
  • Posada M; Institute of Rare Diseases Research, ISCIII, SpainRDR and CIBERER, Madrid, Spain.
  • Taruscio D; National Center for Rare Diseases, Istituto Superiore di Sanità, Rome, Italy.
  • Lochmüller H; John Walton Muscular Dystrophy Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
  • Robinson P; Institute of Medical Genetics, Charité Universitätsmedizin Berlin, Berlin, Germany.
  • Roos M; Leiden University Medical Centre (LUMC), Leiden, Netherlands.
  • Oliveira JL; University of Aveiro, DETI/IEETA, Aveiro, Portugal.
Biomed Res Int ; 2017: 8327980, 2017.
Article em En | MEDLINE | ID: mdl-29214177
Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas de Gerenciamento de Base de Dados / Sistema de Registros / Armazenamento e Recuperação da Informação / Doenças Raras / Web Semântica Limite: Humans Idioma: En Revista: Biomed Res Int Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Portugal País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas de Gerenciamento de Base de Dados / Sistema de Registros / Armazenamento e Recuperação da Informação / Doenças Raras / Web Semântica Limite: Humans Idioma: En Revista: Biomed Res Int Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Portugal País de publicação: Estados Unidos