Research Data Stewardship for Healthcare Professionals

Jansen, P.A.F.; Berg, Linda van den; Overveld, Petra G.M. van; Boiten, Jan-Willem

doi:10.1007/978-3-319-99713-1_4

Cited by 18 publications

(11 citation statements)

References 2 publications

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“…The huge amount of data deriving from different omics analyses need to be adequately collected and stored. Challenges of data management include defining the type of data to be stored and how to store it, the policies for data access, sharing, use, and finally, long-term archiving procedures [ 89 ]. One of the most successful repositories regarding application of multi-omics approach in cancer is NIHs Genome Data Commons (GDC) [ 90 ] containing all data generated by the Cancer Genome Atlas (TCGA) project [ 74 ].…”

Section: Roles Of Computational Approach In Multi-omics Eramentioning

confidence: 99%

Multi-Omics Model Applied to Cancer Genetics

Pettini

Visibelli

Cicaloni

et al. 2021

IJMS

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In this review, we focus on bioinformatic oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. Before providing a deeper insight into the bioinformatics approach and utilities involved in oncology, we must understand what is a system biology framework and the genetic connection, because of the high heterogenicity of the backgrounds of people approaching precision medicine. In fact, it is essential to providing general theoretical information on genomics, epigenomics, and transcriptomics to understand the phases of multi-omics approach. We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field.

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Section: Roles Of Computational Approach In Multi-omics Eramentioning

confidence: 99%

Multi-Omics Model Applied to Cancer Genetics

Pettini

Visibelli

Cicaloni

et al. 2021

IJMS

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show abstract

“…Challenges of data management include defining the type of data to be stored and how to store it; the policies for data access, sharing, and re-use; and long term archiving policies (174). Arguably, the most successful repository of cancer multiomics is NIHs Genome Data Commons (GDC) (175).…”

Section: Data Managementmentioning

confidence: 99%

Computational Oncology in the Multi-Omics Era: State of the Art

Anda-Jáuregui

Hernández‐Lemus

2020

Front. Oncol.

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Cancer is the quintessential complex disease. As technologies evolve faster each day, we are able to quantify the different layers of biological elements that contribute to the emergence and development of malignancies. In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm. In this review, we will focus on computational oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification. We will discuss the machine learning and network approaches as two of the most promising emerging paradigms, in computational oncology. These approaches provide a foundation on how to integrate different layers of biological description into coherent frameworks that allow advances both in the basic and clinical settings.

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“…• Conocimiento de los aspectos legales y éticos de la gestión de datos (Dijkers, 2019;Jansen et al, 2019;Mons, 2018).…”

Section: Competencias Y Tareasunclassified

Gestión de datos de investigación y bibliotecas: preservando los nuevos bienes científicos

2019

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Los datos se han convertido en la base de la infraestructura de la ciencia. La implementación de políticas y servicios de gestión de datos de investigación (GDI) en contextos académicos deviene en factor crítico del éxito organizacional, lo que presenta nuevas oportunidades para el desarrollo de las bibliotecas universitarias y de investigación. A partir de un análisis bibliográfico sobre GDI y bibliotecas y otro exploratorio sobre los servicios de 34 bibliotecas universitarias y de investigación en Europa y América Latina, se extraen los principales puntos de actuación de estas en los procesos de GDI. Para completar el análisis exploratorio, se incluyen los resultados sobre los servicios de identificadores persistentes (PIDs). En muchos casos, los servicios de GDI se convierten en modelos de cooperación con otras unidades institucionales y los investigadores. Asimismo, se discuten las competencias de dos perfiles profesionales necesarios en este contexto: el bibliotecario de datos y el administrador de datos.

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Research Data Stewardship for Healthcare Professionals

Cited by 18 publications

References 2 publications

Multi-Omics Model Applied to Cancer Genetics

Multi-Omics Model Applied to Cancer Genetics

Computational Oncology in the Multi-Omics Era: State of the Art

Gestión de datos de investigación y bibliotecas: preservando los nuevos bienes científicos

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