Ítem
Solo Metadatos

Supervised selection of single nucleotide polymorphisms in chronic fatigue syndrome

Mostrar el registro sencillo de la publicación
dc.creatorCifuentes R.A.spa
dc.creatorBarreto E.spa
dc.date.accessioned2020-05-26T00:02:53Z
dc.date.available2020-05-26T00:02:53Z
dc.date.created2011spa
dc.description.abstractIntroduction: The different ways for selecting single nucleotide polymorphisms have been related to paradoxical conclusions about their usefulness in predicting chronic fatigue syndrome even when using the same dataset. Objective: To evaluate the efficacy in predicting this syndrome by using polymorphisms selected by a supervised approach that is claimed to be a method that helps identifying their optimal profile. Materials and methods: We eliminated those polymorphisms that did not meet the Hardy-Weinberg equilibrium. Next, the profile of polymorphisms was obtained through the supervised approach and three aspects were evaluated: comparison of prediction accuracy with the accuracy of a profile that was based on linkage disequilibrium, assessment of the efficacy in determining a higher risk stratum, and estimating the algorithm influence on accuracy. Results: A valid profile (p less than 0.01) was obtained with a higher accuracy than the one based on linkage disequilibrium, 72.8 vs. 62.2% (p less than 0.01). This profile included two known polymorphisms associated with chronic fatigue syndrome, the NR3C1_11159943 major allele and the 5HTT_7911132 minor allele. Muscular pain or sinus nasal symptoms in the stratum with the profile predicted V with a higher accuracy than those symptoms in the entire dataset, 87.1 vs. 70.4% (p less than 0.01) and 92.5 vs. 71.8% (p less than 0.01) respectively. The profile led to similar accuracies with different algorithms. Conclusions: The supervised approach made it possible to discover a reliable profile of polymorphisms associated with this syndrome. Using this profile, accuracy for this dataset was the highest reported and it increased when the profile was combined with clinical data.eng
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/23537
dc.language.isoengspa
dc.relation.citationEndPage621
dc.relation.citationIssueNo. 4
dc.relation.citationStartPage613
dc.relation.citationTitleBiomedica
dc.relation.citationVolumeVol. 31
dc.relation.ispartofBiomedica, Vol.31, No.4 (2011); pp. 613-621spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84863474887&partnerID=40&md5=08c1ee06202b74a894148aafeba40ccaspa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordArticlespa
dc.subject.keywordChronic fatigue syndromespa
dc.subject.keywordGene linkage disequilibriumspa
dc.subject.keywordGenetic screeningspa
dc.subject.keywordGeneticsspa
dc.subject.keywordHumanspa
dc.subject.keywordMethodologyspa
dc.subject.keywordSingle nucleotide polymorphismspa
dc.subject.keywordFatigue syndromeeng
dc.subject.keywordGenetic testingspa
dc.subject.keywordHumansspa
dc.subject.keywordLinkage disequilibriumspa
dc.subject.keywordPolymorphismeng
dc.subject.keywordArtificial intelligencespa
dc.subject.keywordChronic fatigue syndromespa
dc.subject.keywordComputational biologyspa
dc.subject.keywordGenetic polymorphismspa
dc.subject.keywordLinkage disequilibriumspa
dc.subject.keywordSystems biologyspa
dc.titleSupervised selection of single nucleotide polymorphisms in chronic fatigue syndromespa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
Archivos
Colecciones
Artículos