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SynapticVes-Py. Python code to support 3D quantitative analysis of presynaptic active zones in hippocampal mossy fiber boutons using electron tomograms and IMOD model output.

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KLichter/Lichter-et-al-2022_CellRep_3D-vesicle-python

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Lichter-et-al-2022_CellRep_3D-vesicle-python

This code is intended to support 3D coordinate analysis for IMOD model output of presynaptic active zones in giant hippocampal mossy fiber boutons. IMOD models are based on electron tomograms which were reconstructed using the IMOD software. For further details including how to create IMOD model output please visit https://bio3d.colorado.edu/imod/.

To use the code please follow the instructions in this file and the selected notebook.

  1. download Aanaconda (https://www.anaconda.com/distribution/#download-section).

  2. open Anaconda prompt and create new environment.

conda create --name lichter_tomo-active-zones

activate new environment.

conda activate lichter_tomo-active-zone

install some dependencies.

conda install jupyter scikit-learn sklearn numpy scipy shapely statsmodels 

start jupyter notebook from Anaconda prompt. navigate to and select one of the four notebooks. follow the instructions in the notebook to analyze the exemplary text files (az-test_area/sv-pool/docked-sv-pool).

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SynapticVes-Py. Python code to support 3D quantitative analysis of presynaptic active zones in hippocampal mossy fiber boutons using electron tomograms and IMOD model output.

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