Abstract
Multisite-distributed e-infrastructures can foster computational resources, share brain imaging data, and facilitate data analysis in the study of neurodegenerative diseases. The Global Alzheimer’s Association Interactive Network (GAAIN—https://www.gaain.org) is a platform federating worldwide datasets of the brain. The European side of the GAAIN initiative (EU-GAAIN) exposes five datasets (4051 subjects from E-ADNI/PharmaCOG, I-ADNI, ARWIBO, EDSD, OASIS) currently hosted in the distributed neuGRID e-infrastructure (www.neugrid4you.eu). EU-GAAIN offers a huge amount of morphological and functional scans, surrogate imaging biomarker values (i.e. 4653 cortical and subcortical volumes), cognitive assessments and biochemical markers (i.e.: 286 CSF values, 235 APOE genotype). GAAIN platform provides 24 datasets (almost half million subjects) that can be explored through a user-friendly interface called “GAAIN Interrogator”. Through the GAAIN web-portal, queries results are displayed in graphs and summary tables providing information to understand trends and discover new evidences. The main objective of the GAAIN project is to build a technology for understanding the underlying mechanism of Alzheimer’s disease and other forms of dementia through a data-driven approach. All the GAAIN data mapped in a common data schema are federated through the Data Partner Clients (DPC) and a distributed pipeline enactment service that allows the execution of analyses relying on distributed Docker machines. Research efficiency can be increased if neuroscientists will access secure federated platforms from a single point of access. GAAIN initiative is funded by the Alzheimer’s Association and by National Institutes of Health grants.
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Acknowledgments
This work was supported by the Global Alzheimer’s Association Interactive Network (GAAIN) initiative of the Alzheimer’s Association (grant 003278) and by National Institutes of Health grants 5P41 EB015922-16 and 1U54EB020406-01. The investigators would like to acknowledge Elia Sbeiti for his helpful IT assistance and Margherita Mauri for having polished the English language of the manuscript.
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Orlandi, D., Redolfi, A., Revillard, J., Manset, D., Teipel, S., Frisoni, G.B. (2017). E-Infrastructures for Neuroscientists: The GAAIN and neuGRID Examples. In: Naldi, G., Nieus, T. (eds) Mathematical and Theoretical Neuroscience. Springer INdAM Series, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-68297-6_11
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