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TREES toolbox

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# TREES Toolbox

More than a century ago, Ramón y Cajal provided a qualitative description of neuronal branching in all its forms and variants.
However, even today, few rigorous and useful formalisms are available for quantitative description of dendritic and axonal 
morphology.
The TREES toolbox provides:

1. Tools to automatically reconstruct neuronal branching from microscopy image stacks and to generate synthetic axonal and dendritic trees.
2. The basic tools to edit, visualize and analyze dendritic and axonal trees.
3. Methods for quantitatively comparing branching structures between neurons.
4. Tools for exploring how dendritic and axonal branching depends on local optimization of total wiring and conduction distance.

This software package is written in Matlab (Mathworks, Natick, MA), the most widely used scientific programming language.
We hope that other groups will benefit from this package and that they will add their own code to the TREES toolbox based 
on their own specific applications. The code is therefore freely distributed. When publishing scientific work using this 
toolbox please cite the paper:

```Cuntz H, Forstner F, Borst A, Häusser M (2010). One rule to grow them all: A general theory of neuronal branching and its practical application. PLoS Comput Biol 6(8): e1000877.````

We encourage users of the toolbox to recommend it to their peers (and also to funding and award agencies where appropriate).

# Authors

## Developers

* Hermann Cuntz, Ernst Strüngmann Institute, Frankfurt (main developer)
* Felix Effenberger, Ernst Strüngmann Institute, Frankfurt (developer)
* Marcel Beining, , Ernst Strüngmann Institute, Frankfurt (developer)

## Supervisors

* Alexander Borst, MPI of Neurobiology, Martinsried supervisor
* Michael Häusser, University College London supervisor

## External contributors

* Eilif Müller, EPFL, Blue Brain Project, Lausanne - python wrapping
* Padraig Gleeson, Silver lab, London - neuroML export
* Friedrich Forstner, MPI of Neurobiology, Martinsried developer

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