Modelado computacional de astrocito humano usando datos de transcriptómica y proteómica

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dc.contributor.advisorPinzón Velasco, Andrés Mauricio
dc.contributor.advisorGonzález Santos, Janet
dc.contributor.authorMendoza Mejía, Nicolás
dc.contributor.researchgroupGrupo de Investigación en Bioinformática y Biología de Sistemasspa
dc.date.accessioned2022-07-19T19:56:11Z
dc.date.available2022-07-19T19:56:11Z
dc.date.issued2022-07-17
dc.descriptionilutraciones, graficasspa
dc.description.abstractAunque la astrogliosis está relacionada con eventos neuroprotectores; su neurotoxicidad se ha correlacionado con enfermedades neurodegenerativas y otros desórdenes (Sofroniew & Vinters, 2010). Lo que ha aumentado la atención en el estudio de estas células. Sin embargo, los procesos de señalización y actividad metabólica relacionados con la neurotoxicidad aún son poco conocidos (González et al., 2020; Sofroniew, 2015), por lo que se han empleado modelos metabólicos a escala genómica (GEM) de astrocito para estudiar estas respuestas. Por lo tanto, en este trabajo se hace la contextualización de un GEM de astrocito humano integrando datos multiomicos con una nueva aproximación en combinación con el algoritmo iMAT, permitiendo incluir información de diversos procesos biológicos en el modelo (Karahalil, 2016; Vivek-Ananth & Samal, 2016). En consecuencia, el GEM resultante presenta una mayor cobertura del metabolismo y una capacidad predictiva superior en los escenarios simulados coincidiendo con lo reportado en la literatura. Además, durante la reconstrucción de este modelo se generaron dos algoritmos, uno permite integrar el proteoma y transcriptoma, mientras el otro corrige los desbalances estequiométricos presentes en el modelo. Finalmente, este modelo tiene el potencial de acelerar el estudio de la astrogliosis, permitiendo descifrar la relación entre el metabolismo del astrocito y la aparición de enfermedades neurodegenerativas mediante la generación de hipótesis y la predicción del desempeño de fármacos. (Texto tomado de la fuente)spa
dc.description.abstractEven though astrogliosis is related to neuroprotective events; its neurotoxicity has been correlated with neurodegenerative diseases and other disorders (Sofroniew & Vinters, 2010). Which have shifted the attention towards the study of these cells. However, the related signaling processes and metabolic activity related to the neurotoxicity are still poorly known (González et al., 2020; Sofroniew, 2015), thus genome-scale metabolic models (GEMs) of astrocytes have been used to study this response, as they allow modelling metabolic interac- tions (Martín-Jiménez et al., 2017; Osorio et al., 2020). Therefore, in this work an astrocyte’s GEM is contextualized by integrating multi-omic data with a new approach in combination with the algorithm iMAT, which allows including information from various biological processes in the model (Karahalil, 2016; Vivek-Ananth & Samal, 2016). Thus, the resulting GEM presets a greater coverage of the metabolic net- work and a higher predictive capability in the simulated scenarios, which is in line with the reported data in the literature. In addition, during the reconstruction of this model two algorithms were generated, one integrates the proteome and transcriptome together, meanwhile the other corrects the stoichiometric imbalances present in the model. Finally, this model has the potential to accelerate the study of astrogliosis allowing to decipher the relationship between astrocyte metabolism and the appearance of neurodegenerative diseases by generating hypotheses and predicting drug performance.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Bioinformáticaspa
dc.description.researchareaBiología de sistemasspa
dc.format.extentxii, 73 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/81715
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.departmentDepartamento de Ingeniería de Sistemas e Industrialspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ingeniería - Maestría en Bioinformáticaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.ddc610 - Medicina y saludspa
dc.subject.lembASTROCITOSspa
dc.subject.lembAstrocyteseng
dc.subject.lembINFLAMACIONspa
dc.subject.lembInflammationeng
dc.subject.proposalModelo a escala genómicaspa
dc.subject.proposalAstrocitospa
dc.subject.proposalDatos multi-omicosspa
dc.subject.proposalEnfermedades neurodegenerativasspa
dc.subject.proposalTranscriptómicaspa
dc.subject.proposalProteómicaspa
dc.subject.proposalGenome-scale metabolic modeleng
dc.subject.proposalAstrocyteeng
dc.subject.proposalLipotoxicityeng
dc.subject.proposalNeurodegenerative diseaseseng
dc.subject.proposalTranscriptomicseng
dc.subject.proposalProteomicseng
dc.titleModelado computacional de astrocito humano usando datos de transcriptómica y proteómicaspa
dc.title.translatedComputational modeling of human astrocyte using transcriptomic and proteomic dataeng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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