Managing complex workflows in neural simulation and data analysis
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The importance of tracking metadata
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Table Of Contents
The need for better workflows in data analysis of electrophysiological signals
Reproducible research
Best practices for managing complex workflows: code
Version control
Best practices for managing complex workflows: data
Parallel data analysis
Verification (testing)
Validation: the importance of calibrating statistical correlation methods in data analysis
Provenance tracking
The importance of tracking metadata
Conclusions and outlook
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