A taxonomy of tools and approaches for distributed genomic analyses

The 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...

Full description

Autores:
Garzón, Wilmer
Benavides, Luis Alberto
Gignard, Alban
Südholt, Mario
Tipo de recurso:
Article of journal
Fecha de publicación:
2022
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
eng
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/3156
Acceso en línea:
https://repositorio.escuelaing.edu.co/handle/001/3156
https://repositorio.escuelaing.edu.co/
Palabra clave:
Biometría
Biometry
Análisis de la información
Information analysis
Investigación biomédica
Biomedical research
Tecnología médica
Medical technology
Distributed biomedical analyses
Fully distributed collaborations
Reproducibility
Scalability Multi-site analyses
Distributed workflow analyses
Análisis biomédicos distribuidos
Colaboraciones totalmente distribuidas
Reproducibilidad
Análisis de escalabilidad multisitio
Análisis de flujo de trabajo distribuido
Rights
openAccess
License
http://purl.org/coar/access_right/c_abf2
Description
Summary:The 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.