dc.creator | Nepomuceno Chamorro, Isabel de los Ángeles | es |
dc.creator | Nepomuceno Chamorro, Juan Antonio | es |
dc.creator | Galván Rojas, José Luis | es |
dc.creator | Vega Márquez, Belén | es |
dc.creator | Rubio Escudero, Cristina | es |
dc.date.accessioned | 2022-05-27T09:32:03Z | |
dc.date.available | 2022-05-27T09:32:03Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Nepomuceno Chamorro, I.d.l.Á., Nepomuceno Chamorro, J.A., Galván Rojas, J.L., Vega Márquez, B. y Rubio Escudero, C. (2020). Using prior knowledge in the inference of gene association networks. Applied Intelligence, 50 (11), 3882-3893. | |
dc.identifier.issn | 0924-669X | es |
dc.identifier.uri | https://hdl.handle.net/11441/133798 | |
dc.description.abstract | Traditional computational techniques are recently being improved with the use of prior biological knowledge from open access repositories in the area of gene expression data analysis. In this work, we propose the use of prior knowledge
as heuristic in an inference method of gene-gene associations from gene expression profiles. In this paper, we use Gene
Ontology, which is an open-access ontology where genes are annotated using their biological functionality, as a source of
prior knowledge together with a gene pairwise Gene-Ontology-based measure. The performance of our proposal has been
compared to other benchmark methods for the inference of gene networks, outperforming in some cases and obtaining
similar and competitive results in others, but with the advantage of providing simple and interpretable models, which is a
desired feature for the Artificial Intelligence Health related models as stated by the European Union. | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación TIN2017-88209-C2-2-R | es |
dc.format | application/pdf | es |
dc.format.extent | 11 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Applied Intelligence, 50 (11), 3882-3893. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Gene-gene association networks | es |
dc.subject | Ontology | es |
dc.subject | Semantic similarity measure | es |
dc.subject | Information fusion | es |
dc.subject | Microarray data analysis | es |
dc.title | Using prior knowledge in the inference of gene association networks | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2017-88209-C2-2-R | es |
dc.relation.publisherversion | https://link.springer.com/article/10.1007/s10489-020-01705-4 | es |
dc.identifier.doi | 10.1007/s10489-020-01705-4 | es |
dc.journaltitle | Applied Intelligence | es |
dc.publication.volumen | 50 | es |
dc.publication.issue | 11 | es |
dc.publication.initialPage | 3882 | es |
dc.publication.endPage | 3893 | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | es |