Presenter: Dr. Cengiz Gunay
School of Science and Technology, Georgia Gwinnett College, USA
Showcase time:
| Time zone: | Los Angeles | New York | Berlin | Sydney |
|---|---|---|---|---|
| July 18, 2020 | 3pm | 6pm | midnight | 8am (July 19) |
Description of the software showcase
PANDORA is an open-source toolbox for Matlab (Mathworks, Natick, MA), which has been originally developed for analysis and visualization of single-unit intracellular electrophysiology data (RRID: SCR_001831, Günay et al. 2009 Neuroinformatics, 7(2):93-111. doi: 10.1007/s12021-009-9048-z). Even though there are more modern and popular environments, such as the Python and Anaconda ecosystem, Matlab still offers an advantage in its simplicity, especially towards those less computationally inclined, for instance for collaboration with experimentalists. PANDORA was originally intended for managing and analyzing brute-force neuronal parameter search databases (Günay et al. 2008 J Neurosci. 28(30): 7476-7491; Günay et al. 2010 J Neurosci. 30: 1686–98). However, it has been proven useful for other types of simulation or experimental data analysis (Doloc-Mihu et al. 2011 Journal of biological physics, 37(3), 263–283. doi:10.1007/s10867-011-9215-y; Lin et al. 2012 J Neurosci 32(21): 7267–77; Wolfram et al. 2014 J Neurosci, 34(7): 2538–2543; doi: 10.1523/JNEUROSCI.4511-13.2014; Günay et al. 2015 PLoS Comp Bio. doi: 10.1371/journal.pcbi.1004189; Wenning et al. 2018 eLife 2018;7:e31123 doi: 10.7554/eLife.31123; Günay et al. 2019 eNeuro, 6(4), ENEURO.0417-18.2019. doi:10.1523/ENEURO.0417-18.2019). PANDORA’s original motivation was to offer object-oriented analysis specific to neuronal data inside the Matlab environment, in particular with a database table-like object, similar to R and the Python PANDAS toolbox’s “dataframe” object, and a new syntax for a powerful database querying system. The typical workflow would constitute of generating parameter sets for simulations, and then in the resulting output data, finding spikes and additional characteristics to construct databases, and finally analyze and visualize these database contents. PANDORA provides objects for loading datasets, controlling simulations, importing/exporting data, and visualization. Since it’s inception, it has grown with added functionality. In this showcase, we review the toolbox’s standard features and show how to customize them for a given project, and then introduce some of the new and experimental features, such as ion channel fitting, evolutionary/genetic algorithms. Furthermore, we will give a developers’ perspective for those who may be interested in adding modules to this toolbox.
Software tools
- PANDORA - Github and MathWorks File Exchange pages
Background readings
- Günay et al. 2009 Neuroinformatics, 7(2):93-111. doi: 10.1007/s12021-009-9048-z
- Doloc-Mihu et al. 2011 Journal of Biological Physics, 37(3), 263–283. doi:10.1007/s10867-011-9215-y
- Lin et al. 2012 J Neurosci 32(21): 7267–77
- Wolfram et al. 2014 J Neurosci, 34(7): 2538–2543; doi: 10.1523/JNEUROSCI.4511-13.2014
- Günay et al. 2015 PLoS Comp Bio. doi: 10.1371/journal.pcbi.1004189
- Wenning et al. 2018 eLife 2018;7:e31123 doi: 10.7554/eLife.31123
- Günay et al. 2019 eNeuro, 6(4), ENEURO.0417-18.2019. doi:10.1523/ENEURO.0417-18.2019)
Download materials
Showcase organization
- Pandora introduction and updates
- Tutorials and demo examples
- Q & A feedback