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dc.contributor.authorBacciu, Davide
dc.contributor.authorLisboa, Paulo J G
dc.contributor.authorMartín, José David
dc.contributor.authorStoean, Ruxandra
dc.contributor.authorVellido Alcacena, Alfredo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2018-07-23T06:45:35Z
dc.date.issued2018
dc.identifier.citationBacciu, D., Lisboa, P., Martín, J.D., Stoean, R., Vellido, A. Bioinformatics and medicine in the era of deep learning. A: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. "ESANN 2018: 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges, April 25-26-27 2018: proceedings". I6doc.com, 2018, p. 345-354.
dc.identifier.isbn978-287587047-6
dc.identifier.otherhttps://arxiv.org/abs/1802.09791
dc.identifier.urihttp://hdl.handle.net/2117/119703
dc.description.abstractMany of the current scientific advances in the life sciences have their origin in the intensive use of data for knowledge discovery. In no area this is so clear as in bioinformatics, led by technological breakthroughs in data acquisition technologies. It has been argued that bioinformatics could quickly become the field of research generating the largest data repositories, beating other data-intensive areas such as high-energy physics or astroinformatics. Over the last decade, deep learning has become a disruptive advance in machine learning, giving new live to the long-standing connectionist paradigm in artificial intelligence. Deep learning methods are ideally suited to large-scale data and, therefore, they should be ideally suited to knowledge discovery in bioinformatics and biomedicine at large. In this brief paper, we review key aspects of the application of deep learning in bioinformatics and medicine, drawing from the themes covered by the contributions to an ESANN 2018 special session devoted to this topic.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherI6doc.com
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
dc.subject.lcshKnowledge acquisition (Expert systems)
dc.subject.lcshBioinformatics
dc.subject.lcshMachine learning
dc.subject.otherQuantitative methods
dc.subject.otherKnowledge discovery
dc.subject.otherData acquisition
dc.subject.otherDeep learning
dc.titleBioinformatics and medicine in the era of deep learning
dc.typeConference report
dc.subject.lemacAdquisició del coneixement (Sistemes experts)
dc.subject.lemacBioinformàtica
dc.subject.lemacAprenentatge automàtic
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
drac.iddocument23267405
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/38900TIN2016-79576-R
dc.date.lift10000-01-01
upcommons.citation.authorBacciu, D.; Lisboa, P.; Martín, J.D.; Stoean, R.; Vellido, A.
upcommons.citation.contributorEuropean Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
upcommons.citation.publishedtrue
upcommons.citation.publicationNameESANN 2018: 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges, April 25-26-27 2018: proceedings
upcommons.citation.startingPage345
upcommons.citation.endingPage354


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