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A collaborative approach to develop a multi-omics data analytics platform for translational research

The integration and analysis of large datasets in translational research has become an increasingly challenging problem. We propose a collaborative approach to integrate established data management platforms with existing analytical systems to fill the hole in the value chain between data collection...

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Detalles Bibliográficos
Autores principales: Schumacher, Axel, Rujan, Tamas, Hoefkens, Jens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4888831/
https://www.ncbi.nlm.nih.gov/pubmed/27294023
http://dx.doi.org/10.1016/j.atg.2014.09.010
Descripción
Sumario:The integration and analysis of large datasets in translational research has become an increasingly challenging problem. We propose a collaborative approach to integrate established data management platforms with existing analytical systems to fill the hole in the value chain between data collection and data exploitation. Our proposal in particular ensures data security and provides support for widely distributed teams of researchers. As a successful example for such an approach, we describe the implementation of a unified single platform that combines capabilities of the knowledge management platform tranSMART and the data analysis system Genedata Analyst™. The combined end-to-end platform helps to quickly find, enter, integrate, analyze, extract, and share patient- and drug-related data in the context of translational R&D projects.