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Comparación de modelos de aprendizaje automático para la predicción de células cancerígenas a partir del complejo MHC I

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dc.contributor.advisorOrjuela Cañón, Alvaro David
dc.creatorNavas Luquez, Mateo
dc.creator.degreeIngeniero Biomédicospa
dc.creator.degreetypeFull timespa
dc.date.accessioned2020-05-27T21:38:23Z
dc.date.available2020-05-27T21:38:23Z
dc.date.created2020-05-22
dc.descriptionEl presente trabajo propone una comparación de modelos de aprendizaje automático para la detección de células cancerígenas a partir de los antígenos del complejo MHC I. Utilizando protocolos de extracción de características físico-químicas de las proteínas y un proceso comparativo de las medidas de desempeño en la fase de validación y prueba de los modelos. Con este procedimiento se pretende determinar cuál modelo de aprendizaje automático presenta el mejor desempeño en la predicción de antígenos cancerígenos, utilizando propiedades fisicoquímicas como marcadores de entrada.spa
dc.description.abstractThe present work proposes a comparison of machine learning models for the detection of cancer cells from the MHC I complex antigens. Using protocols for the extraction of physical-chemical characteristics of proteins and a comparative process of performance measurements in the model validation and testing phase. This procedure aims to determine the machine learning model presenting the best performance in the prediction of carcinogenic antigens, using physicochemical properties as input markers.spa
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dc.identifier.doihttps://doi.org/10.48713/10336_24401
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/24401
dc.language.isospaspa
dc.publisherUniversidad del Rosariospa
dc.publisher.departmentEscuela de Medicina y Ciencias de la Saludspa
dc.publisher.programIngeniería Biomédicaspa
dc.rightsAtribución 2.5 Colombiaspa
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dc.rights.urihttp://creativecommons.org/licenses/by/2.5/co/
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dc.source.instnameinstname:Universidad del Rosariospa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocUR
dc.subjectAntígenosspa
dc.subjectAprendizaje automáticospa
dc.subjectCáncerspa
dc.subject.ddcIncidencia & prevención de la enfermedadspa
dc.subject.ddcSistemasspa
dc.subject.keywordAntigenspa
dc.subject.keywordCancerspa
dc.subject.keywordMachine Learningspa
dc.titleComparación de modelos de aprendizaje automático para la predicción de células cancerígenas a partir del complejo MHC Ispa
dc.title.TranslatedTitleComparison of machine learning models for the prediction of cancer cells from the MHC I complexeng
dc.title.alternativePredicción de células cancerígenasspa
dc.typebachelorThesiseng
dc.type.documentAnálisis de casospa
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersion
dc.type.spaTrabajo de gradospa
local.department.reportEscuela de Medicina y Ciencias de la Saludspa
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