Visualitza per autor "Sanz, Ferran"

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  • Bauer-Mehren, Anna; van Mulligen, Erik M.; Avillach, Paul; Carrascosa, María del Carmen; García Serna, Ricard; Piñero González, Janet, 1977-; Singh, Barat; Lopes, Pedro; Oliveira, José Luis; Diallo, Gayo; Ahlberg Helgee, Ernst; Boyer, Scott; Mestres i López, Jordi; Sanz, Ferran; Kors, Jan A.; Furlong, Laura I., 1971- (Public Library of Science (PLoS), 2012)
    Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great ...
  • Flachner, Beáta; Lorincz, Zsolt; Carotti, Angelo; Nicolotti, Orazio; Kuchipudi, Praveena; Kuchipudi, Praveena; Remez Vinogradov, Nikita, 1985-; Sanz, Ferran; Tóvári, József; Szabo, Miklós J; Bertók, Béla; Cseh, Sándor; Mestres i López, Jordi; Dormán, György (Public Library of Science (PLoS), 2012)
    A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity ...
  • Al-Shorbaji, N.; Bellazzi, R.; Gonzalez Bernaldo de Quiros, F.; Koch, Stefanie; Kulikowski, C. A.; Lovell, N.; Maojo, V.; Park, A.; Sanz, Ferran; Sarkar, I. N.; Tanaka, H. (Schattauer, 2016)
    This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "The New Role of Biomedical Informatics in the Age of Digital Medicine" written by Fernando J. Martin-Sanchez and ...
  • 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 ...
  • 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, ...
  • 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 ...
  • Coloma, Preciosa M.; Furlong, Laura I., 1971-; Bauer-Mehren, Anna; Sanz, Ferran; Mestres i López, Jordi; Sturkenboom, Miriam (Public Library of Science (PLoS), 2013)
    Background: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are ...
  • Martí Solano, Maria; Sanz, Ferran; Pastor Maeso, Manuel; Selent, Jana (Public Library of Science (PLoS), 2014)
    Functional selectivity is a property of G protein-coupled receptors that allows them to preferentially couple to particular signaling partners upon binding of biased agonists. Publication of the X-ray crystal structure of ...
  • Cases, Montserrat; Briggs, Katharine; Steger-Hartmann, Thomas; Pognan, François; Marc, Philippe; Kleinöder, Thomas; Schwab, Christof H.; Pastor Maeso, Manuel; Wichard, Jörg; Sanz, Ferran (MDPI, 2014)
    The high-quality in vivo preclinical safety data produced by the pharmaceutical industry during drug development, which follows numerous strict guidelines, are mostly not available in the public domain. These safety data ...
  • Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor Maeso, Manuel (BioMed Central , 2015)
    BACKGROUND: Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models ...
  • Mayer, Miguel Ángel, 1960- (Universitat Pompeu Fabra, 2006-11-02)
    La utilització d'Internet com a font d'informació sanitària és molt freqüent. La qualitat d'aquesta informació és extraordinàriament variable. Els segells de qualitat presents a les webs mediques, concedits per sistemes ...
  • Bauer-Mehren, Anna; Furlong, Laura I., 1971-; Rautschka, Michael; Sanz, Ferran (BioMed Central, 2009)
    Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding ...
  • Lopes, Pedro; Nunes, Tiago; Campos, David; Furlong, Laura I., 1971-; Bauer-Mehren, Anna; Sanz, Ferran; Carrascosa, María del Carmen; Mestres i López, Jordi; Kors, Jan A.; Singh, Barat; van Mulligen, Erik M.; van der Lei, Johan; Diallo, Gayo; Avillach, Paul; Ahlberg Helgee, Ernst; Boyer, Scott; Díaz, Carlos; Oliveira, José Luis (Public Library of Science (PLoS), 2013)
    Pharmacovigilance plays a key role in the healthcare domain through the assessment, monitoring and discovery of interactions amongst drugs and their effects in the human organism. However, technological advances in this ...
  • Mayer, Miguel Ángel, 1960-; Bundschus, Markus; Rautschka, Michael; Sanz, Ferran; Furlong, Laura I., 1971- (Public Library of Science (PLoS), 2011)
    Abstract/nBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not ...
  • Carbonell, Pablo; López, Oriol; Amberg, Alexander; Pastor Maeso, Manuel; Sanz, Ferran (ALTEX Edition, 2017)
    The present study applies a systems biology approach for the in silico predictive modeling of drug toxicity on the basis of high-quality preclinical drug toxicity data with the aim of increasing the mechanistic understanding ...
  • Selent, Jana; Sanz, Ferran; Pastor Maeso, Manuel; De Fabritiis, Gianni (Public Library of Science (PLoS), 2010)
    G-protein coupled receptors, the largest family of proteins in the human genome, are involved in many complex signal transduction pathways, typically activated by orthosteric ligand binding and subject to allosteric ...
  • Briggs, Katharine; Cases, Montserrat; Heard, David J.; Pastor Maeso, Manuel; Pognan, François; Sanz, Ferran; Schwab, Christof H.; Steger-Hartmann, Thomas; Sutter, Andreas; Watson, David K.; Wichard, Jörg (MDPI, 2012)
    There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for ...
  • Bauer-Mehren, Anna (Universitat Pompeu Fabra, 2010-11-08)
    Despite some great success, many human diseases cannot be effectively treated, prevented or cured, yet. Moreover, prescribed drugs are often not very efficient and cause undesired side effects. Hence, there is a need to ...
  • 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 ...
  • Mayer, Miguel Ángel, 1960-; Furlong, Laura I., 1971-; Sanz, Ferran; MedBioinformatics Consortium (Studies in health technology and informatics, 2016)
    Progress in healthcare and biomedical research involves taking advantage of the huge amount of clinical data and biological knowledge that already exists and is currently being generated. Bioinformatic methods and tools ...