Skip to main content

Advertisement

Log in

Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow

  • Software Original Article
  • Published:
Neuroinformatics Aims and scope Submit manuscript

Abstract

We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI’s feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. REST: Representational State Transfer

  2. HDF5: Hierarchical Data Format Version 5; NWB: Neurodata Without Borders; XML: Extended Meta Language; JSON: Javascript Object Notation

  3. https://github.com/SantamariaLab/ABIApiML/blob/master/ExampleScriptABICellData.m

  4. A SimSet is a set of input parameter vectors, each of which is associated with a single simulation. A SimSet may represent many simulations, which will be scheduled to run in parallel on the Simulators in the Simulator Pool. Please see the NeuroManager documents for more details.

  5. Each row in a table has a unique key; a foreign key in a row associates that row with a row in another table. In this way tables support the various characteristics of a thing in a database.

  6. https://github.com/stripathy/AIBS_cell_types

  7. https://github.com/scidash/neuronunit/blob/dev/neuronunit/aibs.py

  8. https://github.com/scidash/neuronunit

  9. http://www.mbfbioscience.com/neurolucida

  10. https://senselab.med.yale.edu/modeldb/

  11. https://www.sqlite.org/

  12. https://github.com/SantamariaLab/NeuroManager

  13. https://github.com/SantamariaLab/ABICellSurvey

  14. https://github.com/SantamariaLab/ABIApiML

  15. http://www.mathworks.com/products/matlab/

References

Download references

Acknowledgements

National Science Foundation (NSF-DBI1451032), National Institutes of Health (NIH-G12MD007591) (for use of computational facilities at UTSA).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David B. Stockton.

Ethics declarations

Conflict of interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Stockton, D., Santamaria, F. Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow. Neuroinform 15, 333–342 (2017). https://doi.org/10.1007/s12021-017-9337-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12021-017-9337-x

Keywords

Navigation