dc.creatorTeixeira, Marlon Amaro Coelho
dc.creatorBelloze, Kele Teixeira
dc.creatorCavalcanti, Maria Cláudia
dc.creatorSilva Junior, Floriano P.
dc.date2018-09-11T15:13:01Z
dc.date2018-09-11T15:13:01Z
dc.date2018
dc.date.accessioned2023-09-26T22:42:42Z
dc.date.available2023-09-26T22:42:42Z
dc.identifierTEIXEIRA, Marlon Amaro Coelho; et al. Data mart construction based on semantic annotation of scientific articles: A case study for the prioritization of drug targets. Computer Methods and Programs in Biomedicine, v.157, p.225–235, Jan. 2018.
dc.identifier0169-2607
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/28655
dc.identifier10.1016/j.cmpb.2018.01.010
dc.identifier1872-7565
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8882237
dc.descriptionSemantic text annotation enables the association of semantic information (ontology concepts) to text expressions (terms), which are readable by software agents. In the scientific scenario, this is particularly useful because it reveals a lot of scientific discoveries that are hidden within academic articles. The Biomedical area has more than 300 ontologies, most of them composed of over 500 concepts. These ontologies can be used to annotate scientific papers and thus, facilitate data extraction. However, in the context of a scientific research, a simple keyword-based query using the interface of a digital scientific texts library can return more than a thousand hits. The analysis of such a large set of texts, annotated with such numerous and large ontologies, is not an easy task. Therefore, the main objective of this work is to provide a method that could facilitate this task.
dc.description2030-01-01
dc.formatapplication/pdf
dc.languageeng
dc.publisherElsevier
dc.rightsrestricted access
dc.subjectSistemas de Suporte à Decisão
dc.subjectPriorização de alvos de drogas
dc.subjectAnotação semântica
dc.subjectSemantic annotation
dc.subjectDecision support systems
dc.subjectDrug target prioritization
dc.titleData mart construction based on semantic annotation of scientific articles: A case study for the prioritization of drug targets
dc.typeArticle


Este ítem pertenece a la siguiente institución