Visualitza per autoria "Queralt Rosinach, Núria"

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  • Decentralized provenance-aware publishing with nanopublications
    Kuhn​, Tobias; Chichester, Christine; Krauthammer, Michael; Queralt Rosinach, Núria; Verborgh, Ruben; Giannakopoulos, George; Ngonga Ngomo, Axel-Cyrille; Viglianti, Raffaele; Dumontier, Michel (PeerJ, 2016)
    Publication and archival of scientific results is still commonly considered the responsability of classical publishing companies. Classical forms of publishing, however, which center around printed narrative articles, no ...
  • DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases.
    Queralt Rosinach, Núria; Piñero González, Janet, 1977-; Bravo Serrano, Àlex, 1984-; Sanz, Ferran; Furlong, Laura I., 1971- (Oxford University Press , 2016)
    MOTIVATION: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable ...
  • DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
    Piñero González, Janet, 1977-; Bravo Serrano, Àlex, 1984-; Queralt Rosinach, Núria; Gutiérrez Sacristán, Alba; Déu Pons, Jordi; Centeno, Emilio; García-García, Javier, 1982-; Sanz, Ferran; Furlong, Laura I., 1971- (Oxford University Press, 2017)
    The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, ...
  • DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes.
    Piñero González, Janet, 1977-; Queralt Rosinach, Núria; Bravo Serrano, Àlex, 1984-; Déu Pons, Jordi; Bauer-Mehren, Anna; Baron, Martin; Sanz, Ferran; Furlong, Laura I., 1971- (Oxford University Press, 2015)
    DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380,000 associations between >16,000 genes and 13,000 ...
  • Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.
    Bravo Serrano, Àlex, 1984-; Piñero González, Janet, 1977-; Queralt Rosinach, Núria; Rautschka, Michael; Furlong, Laura I., 1971- (BioMed Central, 2015)
    BACKGROUND: Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships ...
  • A knowledge-driven approach to extract disease-related biomarkers from the literature
    Bravo Serrano, Àlex, 1984-; Cases, Montserrat; Queralt Rosinach, Núria; Sanz, Ferran; Furlong, Laura I., 1971- (Hindawi, 2014)
    The biomedical literature represents a rich source of biomarker information. However, both the size of literature databases and their lack of standardization hamper the automatic exploitation of the information contained ...
  • Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer
    Sernadela, Pedro; Queralt Rosinach, Núria; Oliveira, José Luis (Hindawi, 2017)
    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 ...
  • Open PHACTS computational protocols for in silico target validation of cellular phenotypic screens: knowing the knowns.
    Digles, Daniela; Queralt Rosinach, Núria; Furlong, Laura I., 1971-; Jacoby, Edgar (Royal Society of Chemistry, 2016)
    Phenotypic screening is in a renaissance phase and is expected by many academic and industry leaders to accelerate the discovery of new drugs for new biology. Given that phenotypic screening is per definition target agnostic, ...
  • The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery
    Dumontier, Michel; Baker, Christopher JO; Baran, Joachim; Callahan, Alison; Chepelev, Leonid; Cruz-Toledo, José; Del Rio, Nicholas R.; Duck, Geraint; Furlong, Laura I., 1971-; Keath, Nichealla; Klassen, Dana; McCusker, Jamie P.; Queralt Rosinach, Núria; Samwald, Matthias; Villanueva-Rosales, Natalia; Wilkinson, Mark; Hoehndorf, Robert (BioMed Central, 2014)
    The Semanticscience Integrated Ontology (SIO) is an ontology to facilitate biomedical knowledge discovery. SIO features a simple upper level comprised of essential types and relations for the rich description of arbitrary ...

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