marissaweis/ssl_neuron
Code to the paper "Self-Supervised Graph Representation Learning for Neuronal Morphologies"
This tool helps neuroscientists and computational biologists analyze and classify neuronal structures. By taking raw neuronal morphology data (like those from the Allen Cell Types Database), it produces meaningful numerical representations of neurons. These representations can then be used for tasks like clustering similar neuron types or predicting their properties, without needing extensive manual labeling of the data.
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Use this if you work with complex 3D neuronal morphology data and need to extract features for classification or analysis without relying on large amounts of pre-labeled data.
Not ideal if you are looking for a tool to visualize neuronal structures or perform basic statistical analysis on simple neuronal measurements.
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Jupyter Notebook
License
MIT
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Last pushed
Apr 05, 2024
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