Pipeline bioinformático para el seguimiento epidemiológico de bacterias multirresistentes dentro de un hospital a partir de genoma completo y datos clínicos
dc.contributor.advisor | Barreto Hernández, Emiliano | |
dc.contributor.author | Prada Padilla, Sebastian | |
dc.contributor.researchgroup | Bioinformática del Instituto de Biotecnología de la Universidad Nacional de Colombia | spa |
dc.coverage.country | Colombia | |
dc.date.accessioned | 2024-01-23T16:26:56Z | |
dc.date.available | 2024-01-23T16:26:56Z | |
dc.date.issued | 2023 | |
dc.description | ilustraciones, diagramas, figuras | spa |
dc.description.abstract | La resistencia a los antimicrobianos es una amenaza de salud pública reconocida a nivel mundial y cobra especial atención en entidades hospitalarias, donde se presentas brotes infecciosos problemáticos por la resistencia de las bacterias y las condiciones de salud de los pacientes, por ello, las entidades hospitalarias implementan medidas de seguimiento epidemiológico para el control y prevención de la propagación de dichas infecciones. En los últimos años los investigadores han optado por incluir información genómica a los estudios epidemiológicos obteniendo resultados más precisos que aportan y podrían mejorar el control de estas infecciones en los hospitales. El objetivo de este trabajo fue diseñar e implementar un pipeline que integre datos clínicos y genómicos para el seguimiento de bacterias dentro de un hospital. Primero se hizo un análisis de requerimientos para determinar los métodos y herramientas bioinformáticas necesarias para el seguimiento con ambos tipos de datos, luego, se diseñó e implementó el pipeline basado en el sistema SGIG, una aplicación web para para la identificación, tipificación y seguimiento de la resistencia a antibióticos desarrolla por el grupo de investigación Bioinformática del Instituto de Biotecnología de la Universidad Nacional de Colombia; y por último, se evaluó la implementación del pipeline en el sistema SGIG con un conjunto de datos clínicos y genómicos provenientes de un hospital. Como resultado el SGIG ahora cuenta con el módulo: Reporte de epidemiologia de precisión, el cual genera un árbol de máxima verosimilitud basado en los SNPs del core genome y relaciona el árbol con una línea de tiempo que representa las estancias de los pacientes en los diferentes sitios del hospital. Este análisis permite hacer un seguimiento epidemiológico más preciso dentro del hospital que mejora el control de las infecciones bacterianas. (Texto tomado de la fuente) | spa |
dc.description.abstract | Antimicrobial resistance is a globally recognized public health threat and receives special attention in hospitals, where infectious outbreaks occur and they are problematic due to the resistance of bacteria and the health conditions of the patients; therefore, hospitals implement epidemiological monitoring measures to control and prevent the spread of these infections. In recent years, researchers have opted to include genomic information to epidemiological studies obtaining more accurate results that provide and could improve the control of these infections in hospitals. The objective of the work is to design and implement a pipeline that integrates clinical and genomic data for the monitoring of bacteria within a hospital, first a requirements analysis was made to determine the methods and bioinformatics tools needed for monitoring with both types of data, then, the pipeline was designed and implemented based on the SGIG system, a web application for the identification, typing and monitoring of antibiotic resistance developed by the Bioinformatica research group of the Instituto de Biotecnología de la Universidad Nacional de Colombia, finally, the implementation of the pipeline in the SGIG system was evaluated with a clinical and genomic dataset from a hospital. As a result, the SGIG now has the module: Precision Epidemiology Report, which generates a maximum likelihood tree based on the SNPs of the core genome and relates the tree to a timeline representing patient stays in the different hospital sites. This analysis allows for more accurate epidemiological monitoring within the hospital that improves bacterial infection control | eng |
dc.description.degreelevel | Maestría | spa |
dc.description.degreename | Magíster en Bioinformática | spa |
dc.description.researcharea | Bioinformática funcional y estructural | spa |
dc.format.extent | xiii, 55 páginas | spa |
dc.format.mimetype | application/pdf | spa |
dc.identifier.instname | Universidad Nacional de Colombia | spa |
dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia | spa |
dc.identifier.repourl | https://repositorio.unal.edu.co/ | spa |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/85409 | |
dc.language.iso | spa | spa |
dc.publisher | Universidad Nacional de Colombia | spa |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá | spa |
dc.publisher.faculty | Facultad de Ingeniería | spa |
dc.publisher.place | Bogotá, Colombia | spa |
dc.publisher.program | Bogotá - Ingeniería - Maestría en Bioinformática | spa |
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dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.rights.license | Reconocimiento 4.0 Internacional | spa |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | spa |
dc.subject.ddc | 570 - Biología::572 - Bioquímica | spa |
dc.subject.decs | Biología Computacional | spa |
dc.subject.decs | Computational Biology | eng |
dc.subject.decs | Farmacorresistencia Microbiana | spa |
dc.subject.decs | Drug Resistance, Microbial | eng |
dc.subject.proposal | Epidemiológica | spa |
dc.subject.proposal | Genómica | spa |
dc.subject.proposal | Infecciones Asociadas a la Atención en Salud (IAAS) | spa |
dc.subject.proposal | Bioinformática | spa |
dc.subject.proposal | Epidemiology | eng |
dc.subject.proposal | Genomics | eng |
dc.subject.proposal | Healthcare-Associated Infections (HAIs) | eng |
dc.subject.proposal | Bioinformatics | eng |
dc.title | Pipeline bioinformático para el seguimiento epidemiológico de bacterias multirresistentes dentro de un hospital a partir de genoma completo y datos clínicos | spa |
dc.title.translated | Bioinformatic pipeline for epidemiological monitoring of multidrug-resistant bacteria within a hospital based on whole genome and clinical data | eng |
dc.type | Trabajo de grado - Maestría | spa |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | spa |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | spa |
dc.type.content | Text | spa |
dc.type.driver | info:eu-repo/semantics/masterThesis | spa |
dc.type.redcol | http://purl.org/redcol/resource_type/TM | spa |
dc.type.version | info:eu-repo/semantics/acceptedVersion | spa |
dcterms.audience.professionaldevelopment | Bibliotecarios | spa |
dcterms.audience.professionaldevelopment | Estudiantes | spa |
dcterms.audience.professionaldevelopment | Investigadores | spa |
dcterms.audience.professionaldevelopment | Maestros | spa |
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dcterms.audience.professionaldevelopment | Personal de apoyo escolar | spa |
dcterms.audience.professionaldevelopment | Público general | spa |
dcterms.audience.professionaldevelopment | Responsables políticos | spa |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 | spa |
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