STATegra
User-driven Development of Statistical Methods for Experimental Planning, Data Gathering, and Integrative Analysis of Next Generation Sequencing, Proteomics and Metabolomics data

Category: European
Funding Agency: EC
Programme: FP7- HEALTH.2012.2.1.1-3- No 306000
Coordinator: Computational Medicine Institute of the Prince Felipe Research Centre (SP)
Start Date: 01.10.2012
Expiration Date: 30.09.2015
Duration: 36 months
Total Budget: 7.853.546 €
FORTH ICS Budget: 702.520€
Related URL: http://www.stategra.eu/
Partners: CLC bio (Denmark), Biomax Informatics AG (Germany), Karolinska Institutet (Sweden), Imperial College of Science, Technology and Medicine (UK), ICS-FORTH Institut d’Investigació Biomèdica de Bellvitge (Spain), University of Amsterdam (Holland), University of Leiden (Holland), the Ludwig-Maximilians University of Munich (Germany), University of California (USA)
Funding Agency: EC
Programme: FP7- HEALTH.2012.2.1.1-3- No 306000
Coordinator: Computational Medicine Institute of the Prince Felipe Research Centre (SP)
Start Date: 01.10.2012
Expiration Date: 30.09.2015
Duration: 36 months
Total Budget: 7.853.546 €
FORTH ICS Budget: 702.520€
Related URL: http://www.stategra.eu/
Partners: CLC bio (Denmark), Biomax Informatics AG (Germany), Karolinska Institutet (Sweden), Imperial College of Science, Technology and Medicine (UK), ICS-FORTH Institut d’Investigació Biomèdica de Bellvitge (Spain), University of Amsterdam (Holland), University of Leiden (Holland), the Ludwig-Maximilians University of Munich (Germany), University of California (USA)
Objectives:
STATegra vision is “that the developments of an appropriate and accurate framework for integratively analyze -omics data will permit a more efficient use of the available information and a better understanding of the results, and that this can only be achieved through an intimate collaboration between statistical experts, biomedical researchers, data producers and software developers”. In the context of the STATegra project, our group will focus its effort in the realization of Integrative Causal Analysis theories, methods and algorithms.