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
复制标题
神经科学网络和软件自动化多学科课程序列开发的经验
DOI:
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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
中科院分区:
文献类型:
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作者:
P. Calyam;S. Nair
—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.
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.