Implementing Workflow Strategies to Handle the Analysis of Complex Electrophysiological Data Sets
Michael Denker (Institute of Neuroscience and Medicine (INM-6), Forschungszentrum Jülich), Andrew Davison (Unité de Neurosciences, Information et Complexité (UNIC), CNRS UPR-3293), Markus Diesmann (Institute of Neuroscience and Medicine (INM-6), Forschungszentrum Jülich), Sonja Grün (Institute of Neuroscience and Medicine (INM-6), Forschungszentrum Jülich)
Here, we showcase experiences in establishing good-practice workflows and building corresponding tool-chains to facilitate the handling of electrophysiological data. We demonstrate how we combine and amend various software tools, both generic (e.g., version control systems, parallelization libraries ...) and specifically from the neuroinformatics community (e.g., lab journaling systems such as sumatra ), to achieve an efficient working style that is flexible, leads to reproducible results, and is open for collaboration.
In parallel to our own efforts, we present results from two initiatives aimed at sampling the current state of maturation of workflows in the electrophysiology community. First, we analyze an on-line survey pinpointing the major problems encountered in the analysis of high-dimensional data sets. Second, we report hands-on insights sampled from several laboratories gained during a workshop on workflows in electrophysiology.
Acknowledgements: Supported by the European Union (FP7-ICT-2009-6, BrainScaleS).
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