Resources

Resources

SecureData4Health (SD4Health) is a secure cloud infrastructure for the analysis and sharing of epi/genomic and health data. By establishing a database platform on SD4Health, we are addressing the needs of our members who have large datasets, but lack the computational and analytical infrastructure required for biomedical research. SD4Health’s infrastructure (10,272 CPU cores, 60 GPUs, 23.7 PB of online storage, security policies and software, privacy protection, all integrated into existing data centers) will pave the way for major advances in supporting a range of research and translational projects that generate data, but currently lack adequate computational and analytical resources. The SD4Health platform will support current and future projects, amplify our ability to use and share new and existing genomic and health data, and foster clinical investigations and biomedical research.

On the network website, researchers will have access to a directory containing existing animal models, cell lines, transgenic models, available tissues and corresponding datasets. Currently, many researchers in the network use the same models in DOHaD research, for example parental exposure to high-fat diets or micronutrient deficiency. This searchable database will link researchers using the same models, but with different interests (e.g. specific tissues), to maximize the use of research funds while reducing the number of animals, and foster collaborations.

 The Maelstrom platform (www.maelstrom-research.org) aims to 1) optimize the use of research data by providing access to an international catalog of studies and variables, and 2) facilitate the management of collaborative research projects by offering free access to software and methodologies to harmonize, integrate and document research data easily and cost-effectively. These tools have been developed over the past 20 years by a group of researchers led by Dr Isabel Fortier. ODISÉ network researchers conduct large-scale birth cohort studies, and will collaborate with the Maelstrom team to optimize the use of research data and data acquisition models. This collaboration will, for example, make it possible to establish recommendations on the essential information to be collected and the procedures recommended for these cohort studies covering the periconception, pregnancy and childhood periods 

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