Experiences from a Multi-disciplinary Course Sequence Development on Cyber and Software Automation in Neuroscience

Experiences from a Multi-disciplinary Course Sequence Development on Cyber and Software Automation in Neuroscience
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神经科学网络和软件自动化多学科课程序列开发的经验

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发表时间:
2018
期刊:
影响因子:
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通讯作者:
S. Nair
S. Nair
中科院分区:
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文献类型:
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作者:
P. Calyam;S. Nair

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-神经科学家越来越依赖并行和分布式计算资源来分析和可视化他们的神经元模拟。这需要编程和网络基础设施配置方面的专业知识,这超出了大多数神经科学项目的能力范围。本文介绍了密苏里大学一学分研究生研究培训课程ECE8001“神经科学中的软件和网络自动化”的早期经验,该课程旨在促进计算神经科学和网络基础设施学生和教职员工之间的多学科合作。具体地说,我们讨论了课程组织和范例结果,涉及下一代科学门户,用于培训新手用户关于范例神经科学用例,涉及使用工具,如神经元和fi关于本地和神经科学门户资源。我们还讨论了我们的愿景,即为生物/心理科学和计算机科学/工程专业的研究生/本科生提供课程序列课程,利用Jupyter Notebook平台共同构建“自助式”培训模块。因此,我们的努力展示了我们如何为Fullfi创建可扩展和可持续的网络和软件自动化,以及广泛的神经科学研究和教育用例。
—Neuroscientists are increasingly relying on parallel and distributed computing resources for analysis and visualization of their neuron simulations. This requires expert knowledge of programming and cyberinfrastructure configuration, which is beyond the repertoire of most neuroscience programs. This paper presents early experiences from a one-credit graduate research training course titled ECE 8001 “Software and Cyber Automation in Neuroscience” at the University of Missouri for engendering multi-disciplinary collaborations between computational neuroscience and cyberinfrastructure students and faculty. Specifically, we discuss the course organization and exemplar outcomes involving a next-generation science gateway for training novice users on exemplar neuroscience use cases that involve using tools such as NEURON and MATLAB on local as well as Neuroscience Gateway resources. We also discuss our vision towards a course sequence curriculum for graduate/undergraduate students from biological/psychological sciences and computer science/engineering to jointly build “self-service” training modules using Jupyter Notebook platforms. Thus, our efforts show how we can create scalable and sustainable cyber and software automation for fulfilling a broad set of neuroscience research and education use cases.
DOI: 10.1109/te.2018.2859411
发表时间: 2019-03
影响因子: 2.6
作者:
Latimer, Benjamin;Bergin, David A.;Guntu, Vinay;Schulz, David J.;Nair, Satish S.
通讯作者: Nair, Satish S.