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Twin Res. 2003 Oct;6(5):383-90.

Data modeling and data communication in GenomEUtwin.

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  • 1Department of Medical Epidemiology and Biostatistics, Karolinska Insitutet, Stockholm, Sweden.


Database infrastructure has become a critical component for competitive life sciences research and discovery. The explosion of data requires that the data are properly loaded, accessed, managed, queried, analyzed, and shared with others. The key purpose of the population-based twin cohorts housed at different institutions in Europe is to gather an extremely large quantity of information from their twin populations, and share it. Longitudinal research over a long period of time, hopefully generations, demands completely new methods and systems to handle the gathering of information and storing. These cohorts bring to the fore problems concerning the need for a standardization of research data and a computer and storage strategy. In the following we describe the preliminary strategy being implemented in the Database Core of GenomEUtwin.

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