dimitri-yatsenko/datajoint-elements

DataJoint Elements is a collection of curated computational workflow for neurophysiology experiments.

DataJoint Elements for Neurophysiology

DataJoint Elements provides an efficient approach for neuroscience labs to create and manage scientific data workflows: the complex multi-step methods for data collection, preparation, processing, analysis, and modeling that researchers must perform in the course of an experimental study. The work is derived from the developments in leading neuroscience projects and uses the DataJoint framework for defining, deploying, and sharing their data workflows.

DataJoint

the open-source framework for data pipelines and automated computational workflows + related documentation, tools, and utilities.

DataJoint Elements

a collection of curated modules for assembling workflows for the major modalities of neurophysiology experiments + related documentation, tools, and utilities.

An overview of the principles of DataJoint workflows and the goals of DataJoint Elements are described in the position paper "DataJoint Elements: Data Workflows for Neurophysiology".

Project Structure

• Management and Policies
• Design Principles
• Guidelines for Adoption
• Glossary

DataJoint Elements

• Lab management
• Animal management
• Experiment session
  • Example workflow for lab, subject and session management
• Extracellular array electrophysiology for Neuropixels
  • Example workflow
• Calcium imaging
  • Example workflow
• Miniscope imaging
  • Example workflow

DataJoint Elements -- in development

• DeepLabCut
• Trial-based experiments
• Electrode localization for Neuropixels
• Facemap

DataJoint framework

• DataJoint for Python
• DataJoint for MATLAB
• DataJoint Documentation
• DataJoint Tutorials
• Docker image for MySQL server configured for use with DataJoint

DataJoint Interfaces

• Pharus — a REST API for interacting with DataJoint databases
• DataJoint LabBook — a front-end web interface for viewing and entering data
• DataJoint SciViz — a low-code framework for building websites for interactive data visualizaion.

DataJoint Online Training

• DataJoint CodeBook - interactive online tutorials

Citation

If your work uses DataJoint or DataJoint Elements, please cite the following:

DataJoint

Yatsenko D, Reimer J, Ecker AS, Walker EY, Sinz F, Berens P, Hoenselaar A, Cotton RJ, Siapas AS, Tolias AS. DataJoint: managing big scientific data using MATLAB or Python. bioRxiv. 2015 Jan 1:031658.

DataJoint Elements

Yatsenko D, Nguyen T, Shen S, Gunalan K, Turner CA, Guzman R, Sasaki M, Sitonic D, Reimer J, Walker EY, Tolias AS. DataJoint Elements: Data Workflows for Neurophysiology. bioRxiv. 2021 Jan 1.