Thanks to the new advanced tools and the innovative methods to image deep in the brain at cell resolution, neuroanatomy is quickly redefining its protocols for quantitatively studying neurons in their own three-dimensional arrangement. The huge amount of data generated has to be managed and shared among labs: this need has led us to develop DataBrain, an on-line archive of three-dimensional single neuron reconstructions and their associated morphometrics. DataBrain interface allows users to upload and download data, to easily search neuron using filters and to on-line view both three-dimensional reconstructions and morphological parameters. Here we describe DataBrain's main features and show an example of how it can be used to store morphological quantitative datasets of Purkinje cells from murine clarified cerebellum slices acquired using a confocal microscope.

Databrain: A web-accessible database for three-dimensional reconstructions and quantitative morphometrics of neurons

Magliaro, Chiara;Callara, A. L.;De Maria, C.;Ferrari, V.;Vanello, N.;Tognetti, A.;Vaglini, F.;Castagna, M.;De Rossi, D.;Landini, L.;Ahluwalia, A.
2017-01-01

Abstract

Thanks to the new advanced tools and the innovative methods to image deep in the brain at cell resolution, neuroanatomy is quickly redefining its protocols for quantitatively studying neurons in their own three-dimensional arrangement. The huge amount of data generated has to be managed and shared among labs: this need has led us to develop DataBrain, an on-line archive of three-dimensional single neuron reconstructions and their associated morphometrics. DataBrain interface allows users to upload and download data, to easily search neuron using filters and to on-line view both three-dimensional reconstructions and morphological parameters. Here we describe DataBrain's main features and show an example of how it can be used to store morphological quantitative datasets of Purkinje cells from murine clarified cerebellum slices acquired using a confocal microscope.
2017
9789811051210
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/880891
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