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Semantic similarity across biomedical ontologies

datacite.subject.fosCiências Naturais::Ciências da Computação e da Informaçãopt_PT
dc.contributor.advisorCouto, Francisco José Moreira
dc.contributor.authorFerreira, João Diogo Silva, 1986-
dc.date.accessioned2016-11-17T17:03:39Z
dc.date.available2016-11-17T17:03:39Z
dc.date.issued2016
dc.date.submitted2015
dc.descriptionTese de doutoramento, Informática (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2016pt_PT
dc.description.abstractThe need to compare complex entities is relevant in all the areas of science. In medicine, for example, comparing a clinical case to a database of previous cases can be extremely helpful when trying to diagnose a disease or deciding the most appropriate treatment for a patient. Recent developments in knowledge representation, in particular the creation of the Web Ontology Language (OWL), have lead to a rise in the amount of knowledge that is being stored in ontologies, which represent, in machine-readable format, the known facts about reality. With the help of ontologies, statements like “Influenza is an Infectious disease” can be processed by computers, which, in turn, can be used to create new knowledge. In particular, semantic similarity has emerged to explore these ontologies as a way to compare entities annotated with the ontology concepts. Semantic similarity has been extensively studied in the last decade, but some problems still persist. While there are algorithms to compare entities annotated with concepts from the same ontology, the possible ways to use more than one ontology are still in an early phase of study. For example, comparing a metabolic pathway using both the associated molecular functions and the metabolites converted in the pathway should, in principle, yield a higher precision than would be achieved with methodologies that rely on either one of the two domains independently. Comparing concepts from different domains and entities annotated with concepts from different domains is yet an unexplored area, but necessary to tackle multidisciplinary biomedical resources, e. g. to compare two clinical cases, the relationships between symptoms, diseases, blood screening results, etc. should provide a more insightful and precise value of similarity. In this document, I explain the basic concepts needed to understand the problem of semantic similarity, how it is being solved, and how I propose to extend this notion so that it can be applied to more than one ontology and, more significantly, to more than one domain of knowledge.pt_PT
dc.identifier.tid101324634pt_PT
dc.identifier.urihttp://hdl.handle.net/10451/25070
dc.language.isoengpt_PT
dc.subjectBiomedicinapt_PT
dc.subjectBioinformáticapt_PT
dc.subjectSemântica de computadorespt_PT
dc.subjectOntologiapt_PT
dc.subjectTeses de doutoramento - 2016pt_PT
dc.titleSemantic similarity across biomedical ontologiespt_PT
dc.typedoctoral thesis
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F69345%2F2010/PT
oaire.fundingStreamSFRH
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typedoctoralThesispt_PT
relation.isProjectOfPublicationf52dbed2-5478-46a5-b714-47bbca0f8cee
relation.isProjectOfPublication.latestForDiscoveryf52dbed2-5478-46a5-b714-47bbca0f8cee
thesis.degree.nameDoutoramento em Informáticapt_PT

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