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Chapitre D'ouvrage Année : 2023

Main Existing Datasets for Open Brain Research on Humans

Mulusew Fikere
Joshua Harvey
Penelope Lind
Lachlan Strike
Margie Wright

Résumé

Recent advances in technology have made possible to quantify fine-grained individual differences at many levels, such as genetic, genomics, organ level, behavior, and clinical. The wealth of data becoming available raises great promises for research on brain disorders as well as normal brain function, to name a few, systematic and agnostic study of disease risk factors (e.g., genetic variants, brain regions), the use of natural experiments (e.g., evaluate the effect of a genetic variant in a human population), and unveiling disease mechanisms across several biological levels (e.g., genetics, cellular gene expression, organ structure and function). However, this data revolution raises many challenges such as data sharing and management, the need for novel analysis methods and software, storage, and computing. Here, we sought to provide an overview of some of the main existing human datasets, all accessible to researchers. Our list is far from being exhaustive, and our objective is to publicize data sharing initiatives and help researchers find new data sources.
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hal-04254339 , version 1 (23-10-2023)

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Baptiste Couvy-Duchesne, Simona Bottani, Etienne Camenen, Fang Fang, Mulusew Fikere, et al.. Main Existing Datasets for Open Brain Research on Humans. Olivier Colliot. Machine Learning for Brain Disorders, Springer US, pp.753-804, 2023, ⟨10.1007/978-1-0716-3195-9_24⟩. ⟨hal-04254339⟩
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