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79	79	**Level**: advanced(%%) **Type**: user documentation
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	81	+=== [[Using the CellBuilder – Introduction>>https://neuron.yale.edu/neuron/static/docs/cbtut/main.html||rel=" noopener noreferrer" target="_blank"]] ===
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	83	+**Level**: advanced(%%) **Type**: interactive tutorial
	84	+
	85	+The following tutorials show how to use the CellBuilder, a powerful and convenient tool for constructing and managing models of individual neurons. It breaks the job of model specification into a sequence of tasks:
	86	+1. Setting up model topology (branching pattern).
	87	+2. Grouping sections with shared properties into subsets.
	88	+3. Assigning geometric properties (length, diameter) to subsets or individual sections, and specifying a discretization strategy (i.e. how to set nseg).
	89	+4. Assigning biophysical properties (Ra, cm, ion channels, buffers, pumps, etc.) to subsets or individual sections.
	90	+=== [[Using Import3D – Exploring morphometric data and fixing problems>>https://neuron.yale.edu/neuron/docs/import3d/fix_problems||rel=" noopener noreferrer" target="_blank"]] ===
	91	+
	92	+**Level**: advanced(%%) **Type**: user documentation
	93	+
	94	+Import3D tool can be used to translate common varieties of cellular morphometric data into a CellBuilder that specifies the anatomical properties of a model neuron. This Tutorial will guide you through how to fix problems in your morphometric data.
	95	+=== [[Randomness in NEURON models– The solution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] ===
	96	+
	97	+**Level**: advanced(%%) **Type**: user documentation
	98	+
	99	+In this part of the tutorial we will show you how to give NetStim its own random number generator.
	100	+=== [[Segmentation intro: Dealing with simulations that generate a lot of data>>https://neuron.yale.edu/neuron/docs/dealing-simulations-generate-lot-data||rel=" noopener noreferrer" target="_blank"]] ===
	101	+
	102	+**Level**: advanced(%%) **Type**: user documentation
	103	+
	104	+How to deal with simulations that generate a lot of data that must be saved? We will showcase different approaches.
	105	+=== [[Using the Channel Builder – Creating a channel from an HH-style specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/hhstyle/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	106	+
	107	+**Level**: advanced(%%) **Type**: interactive tutorial
	108	+
	109	+Our goal is to implement a new voltage-gated macroscopic current whose properties are described by HH-style equations.
	110	+=== [[Using the Channel Builder – Creating a channel from a kinetic scheme specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/kinetic/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	111	+
	112	+**Level**: advanced(%%) **Type**: interactive tutorial
	113	+
	114	+Here we will implement a new voltage-gated macroscopic current whose properties are described by a family of chemical reactions.
	115	+