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Toward Community-Driven Big Open Brain Science: Open Big Data and Tools for Structure, Function, and Genetics.
Annual Review of Neuroscience ( IF 13.9 ) Pub Date : 2020-07-08 , DOI: 10.1146/annurev-neuro-100119-110036
Adam S Charles 1, 2 , Benjamin Falk 1 , Nicholas Turner 3 , Talmo D Pereira 4 , Daniel Tward 1 , Benjamin D Pedigo 1 , Jaewon Chung 1 , Randal Burns 1 , Satrajit S Ghosh 5, 6 , Justus M Kebschull 1, 7 , William Silversmith 4 , Joshua T Vogelstein 1, 2
Affiliation  

As acquiring bigger data becomes easier in experimental brain science, computational and statistical brain science must achieve similar advances to fully capitalize on these data. Tackling these problems will benefit from a more explicit and concerted effort to work together. Specifically, brain science can be further democratized by harnessing the power of community-driven tools, which both are built by and benefit from many different people with different backgrounds and expertise. This perspective can be applied across modalities and scales and enables collaborations across previously siloed communities.

中文翻译:


走向社区驱动的大开放脑科学:开放大数据和结构、功能和遗传学工具。

随着在实验性脑科学中获取更大的数据变得更加容易,计算和统计脑科学必须取得类似的进步才能充分利用这些数据。解决这些问题将受益于更加明确和一致的共同努力。具体来说,脑科学可以通过利用社区驱动工具的力量来进一步民主化,这些工具都是由具有不同背景和专业知识的许多不同人构建并受益于这些工具的。这种观点可以跨模式和规模应用,并支持以前孤立的社区之间的协作。

更新日期:2020-07-09
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