Quantitative neuronal morphometry by supervised and unsupervised learning

We present a protocol to characterize the morphological properties of individual neurons reconstructed from microscopic imaging. We first describe a simple procedure to extract relevant morphological features from digital tracings of neural arbors. Then, we provide detailed steps on classification,...

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Detalles Bibliográficos
Autores principales: Bijari, Kayvan, Valera, Gema, López-Schier, Hernán, Ascoli, Giorgio A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496329/
https://www.ncbi.nlm.nih.gov/pubmed/34647039
http://dx.doi.org/10.1016/j.xpro.2021.100867

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496329/
https://www.ncbi.nlm.nih.gov/pubmed/34647039
http://dx.doi.org/10.1016/j.xpro.2021.100867

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