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Data Modeling and Data Communication in GenomEUtwin

Published online by Cambridge University Press:  21 February 2012

Jan-Eric Litton ,
Juha Muilu ,
Ann Björklund ,
Anne Leinonen  and
Nancy L. Pedersen
Jan-Eric Litton*
Affiliation:
Department of Medical Epidemiology and Biostatistics, Karolinska Insitutet, Stockholm, Sweden. Jan-eric.Litton@mep.ki.se
Juha Muilu
Affiliation:
Finnish Genome Center, Biomedicum Helsinki, University of Helsinki, Finland.
Ann Björklund
Affiliation:
Department of Medical Epidemiology and Biostatistics, Karolinska Insitutet, Stockholm, Sweden.
Anne Leinonen
Affiliation:
Finnish Genome Center, Biomedicum Helsinki, University of Helsinki, Finland.
Nancy L. Pedersen
Affiliation:
Department of Medical Epidemiology and Biostatistics, Karolinska Insitutet, Stockholm, Sweden.
*
*Address for correspondence: Jan-Eric Litton, Department of Medical Epidemiology and Biostatistics, P.O. Box 281, Karolinska Insitutet, SE-171 77 Stockholm, Sweden.

Abstract

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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.

Type
Articles
Information
Twin Research and Human Genetics , Volume 6 , Issue 5 , 01 October 2003 , pp. 383 - 390
Copyright
Copyright © Cambridge University Press 2003