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How Big Data and High-Performance Computing Drive Brain Science
Author(s) -
Shanyu Chen,
Zhipeng He,
Xinyin Han,
Xiaoyu He,
Ruilin Li,
Haidong Zhu,
Dan Zhao,
Chuangchuang Dai,
Yu Zhang,
Zhonghua Lu,
Xuebin Chi,
Beifang Niu
Publication year - 2019
Publication title -
genomics proteomics and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.114
H-Index - 49
eISSN - 2210-3244
pISSN - 1672-0229
DOI - 10.1016/j.gpb.2019.09.003
Subject(s) - big data , computer science , data science , operating system
Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.

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