Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis.
Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis.
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DOI:
10.1016/j.neuron.2022.06.018
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发表时间:
2022-09-07
期刊:
影响因子:
16.2
通讯作者:
Cunningham, John P.
中科院分区:
文献类型:
--
作者:
Abe, Taiga;Kinsella, Ian;Saxena, Shreya;Buchanan, E. Kelly;Couto, Joao;Briggs, John;Kitt, Sian Lee;Glassman, Ryan;Zhou, John;Paninski, Liam;Cunningham, John P.
A key aspect of neuroscience research is the development of powerful, general-purpose data analyses that process large datasets. Unfortunately, modern data analyses have a hidden dependence upon complex computing infrastructure (e.g. software and hardware), which acts as an unaddressed deterrent to analysis users. While existing analyses are increasingly shared as open source software, the infrastructure and knowledge needed to deploy these analyses efficiently still pose significant barriers to use. In this work we develop Neuroscience Cloud Analysis As a Service (NeuroCAAS ): a fully automated open-source analysis platform offering automatic infrastructure reproducibility for any data analysis. We show how NeuroCAAS supports the design of simpler, more powerful data analyses, and that many popular data analysis tools offered through NeuroCAAS outperform counterparts on typical infrastructure. Pairing rigorous infrastructure management with cloud resources, NeuroCAAS dramatically accelerates the dissemination and use of new data analyses for neuroscientific discovery. Computing infrastructure is a fundamental part of neural data analysis. Abe et al. present an open source, cloud based platform called NeuroCAAS to automatically build reproducible computing infrastructure for neural data analysis. They show that NeuroCAAS supports novel analysis design and can improve the efficiency of popular existing methods.
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影响因子:
12.3
作者:
Carpenter AE;Jones TR;Lamprecht MR;Clarke C;Kang IH;Friman O;Guertin DA;Chang JH;Lindquist RA;Moffat J;Golland P;Sabatini DM
通讯作者:
Sabatini DM
影响因子:
48
作者:
Amezquita, Robert A.;Lun, Aaron T. L.;Hicks, Stephanie C.
通讯作者:
Hicks, Stephanie C.
影响因子:
48
作者:
de Chaumont, Fabrice;Dallongeville, Stephane;Olivo-Marin, Jean-Christophe
通讯作者:
Olivo-Marin, Jean-Christophe
影响因子:
19.6
作者:
Chen, Xiaoli;Dallmeier-Tiessen, Suenje;Neubert, Sebastian
通讯作者:
Neubert, Sebastian
DOI:
10.1007/3-540-45014-9_1
发表时间:
2000-01-01
期刊:
MULTIPLE CLASSIFIER SYSTEMS
影响因子:
--
作者:
Dietterich, TG
通讯作者:
Dietterich, TG