A collaborative approach to develop a multi-omics data analytics platform for translational research. Schumacher, A., Rujan, T., & Hoefkens, J. Applied & translational genomics, 3(4):105–108, December, 2014.
doi  abstract   bibtex   
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.
@article{schumacher_collaborative_2014,
	title = {A collaborative approach to develop a multi-omics data analytics platform for translational research.},
	volume = {3},
	issn = {2212-0661},
	doi = {10.1016/j.atg.2014.09.010},
	abstract = {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.},
	language = {eng},
	number = {4},
	journal = {Applied \& translational genomics},
	author = {Schumacher, Axel and Rujan, Tamas and Hoefkens, Jens},
	month = dec,
	year = {2014},
	pmid = {27294023},
	pmcid = {PMC4888831},
	keywords = {Data analytics, Data sharing, Integration, Omics, Scalability, Translational research},
	pages = {105--108},
}

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