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A taxonomy of tools and approaches for distributed genomic analyses

dc.contributor.authorGarzón, Wilmer
dc.contributor.authorBenavides, Luis Alberto
dc.contributor.authorGignard, Alban
dc.contributor.authorSüdholt, Mario
dc.date.accessioned2024-07-11T16:51:03Z
dc.date.available2024-07-11T16:51:03Z
dc.date.issued2022
dc.identifier.urihttps://repositorio.escuelaing.edu.co/handle/001/3156
dc.description.abstractThe amount of biomedical data collected and stored has grown significantly. Analyzing these extensive amounts of data cannot be done by individuals or single organizations anymore. Thus, the scientific community is creating global collaborative efforts to analyze these data. However, biomedical data is subject to several legal and socio- economic restrictions hindering the possibilities for research collaboration. In this paper, we argue that researchers require new tools and techniques to address the restrictions and needs of global scientific collaborations over geo-distributed biomedical data. These tools and techniques must support what we call Fully Distributed Collaborations (FDC), which are research endeavors that harness means to exploit and analyze massive biomedical information collaboratively while respecting legal and socio-economical restrictions. This paper first motivates and discusses the requirements of FDCs in the context of a research collaboration on the development of diagnostic and predictive tools for the risk of intracranial aneurysm formation and rupture (the ICAN project). The paper then presents a taxonomy classifying the current tools and techniques for biomedical analysis with respect to the proposed requirements. The taxonomy considers three key architectural features to support FDC scenarios: data and computation placement, Privacy and Security, and Performance and Scalability. The review reveals new research opportunities to design tools and techniques for multi-site analyses encouraging scientific collaborations while mitigating technical and legal constraints.eng
dc.description.abstractLa cantidad de datos biomédicos recopilados y almacenados ha aumentado significativamente. El análisis de estas grandes cantidades de datos ya no lo pueden realizar individuos ni organizaciones individuales. Así, la comunidad científica está creando esfuerzos colaborativos globales para analizar estos datos. Sin embargo, los datos biomédicos están sujetos a varias restricciones legales y socioeconómicas que obstaculizan las posibilidades de colaboración en investigación. En este artículo, sostenemos que los investigadores necesitan nuevas herramientas y técnicas para abordar las restricciones y necesidades de las colaboraciones científicas globales sobre datos biomédicos geodistribuidos. Estas herramientas y técnicas deben respaldar lo que llamamos Colaboraciones Totalmente Distribuidas (FDC), que son esfuerzos de investigación que aprovechan los medios para explotar y analizar información biomédica masiva de manera colaborativa respetando las restricciones legales y socioeconómicas. En primer lugar, este artículo motiva y analiza los requisitos de los CDF en el contexto de una colaboración de investigación sobre el desarrollo de herramientas de diagnóstico y predicción del riesgo de formación y rotura de aneurismas intracraneales (el proyecto ICAN). Luego, el artículo presenta una taxonomía que clasifica las herramientas y técnicas actuales para el análisis biomédico con respecto a los requisitos propuestos. La taxonomía considera tres características arquitectónicas clave para admitir escenarios FDC: ubicación de datos y cálculos, privacidad y seguridad, y rendimiento y escalabilidad. La revisión revela nuevas oportunidades de investigación para diseñar herramientas y técnicas para análisis multisitio que fomenten colaboraciones científicas y al mismo tiempo mitiguen las limitaciones técnicas y legales.spa
dc.format.extent17 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherElsevier Ltdspa
dc.sourcewww.elsevier.com/locate/imuspa
dc.titleA taxonomy of tools and approaches for distributed genomic analyseseng
dc.typeArtículo de revistaspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.contributor.researchgroupCTG - Informáticaspa
dc.identifier.eissn2352-9148spa
dc.identifier.instnameUniversidad Escuela Colombiana de Ingeniería Julio Garavitospa
dc.identifier.reponameRepositorio Digitalspa
dc.identifier.repourlhttps://repositorio.escuelaing.edu.co/spa
dc.publisher.placeBogotá (Colombia)spa
dc.relation.citationeditionVol. 32 año 2022spa
dc.relation.citationendpage17spa
dc.relation.citationstartpage1spa
dc.relation.citationvolume32spa
dc.relation.ispartofjournalInformatics in Medicine Unlockedeng
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.subject.armarcBiometría
dc.subject.armarcBiometry
dc.subject.armarcAnálisis de la información
dc.subject.armarcInformation analysis
dc.subject.armarcInvestigación biomédica
dc.subject.armarcBiomedical research
dc.subject.armarcTecnología médica
dc.subject.armarcMedical technology
dc.subject.proposalDistributed biomedical analyseseng
dc.subject.proposalAnálisis biomédicos distribuidosspa
dc.subject.proposalFully distributed collaborationseng
dc.subject.proposalColaboraciones totalmente distribuidasspa
dc.subject.proposalReproducibilityeng
dc.subject.proposalReproducibilidadspa
dc.subject.proposalScalability Multi-site analyseseng
dc.subject.proposalAnálisis de escalabilidad multisitiospa
dc.subject.proposalDistributed workflow analyseseng
dc.subject.proposalAnálisis de flujo de trabajo distribuidospa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa


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