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92	92	**Level**: advanced(%%) **Type**: user documentation
93	93
94	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	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		-=== [[Randomness in NEURON models– Source code that demonstrates the solution>>https://neuron.yale.edu/neuron/docs/source-code-demonstrates-solution||rel=" noopener noreferrer" target="_blank"]] ===
116		-
117		-**Level**: advanced(%%) **Type**: user documentation
118		-
119		-=== [[Using the Network Builder – Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===
120		-
121		-**Level**: advanced(%%) **Type**: user documentation
122		-
123		-=== [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===
124		-
125		-**Level**: advanced(%%) **Type**: user documentation
126		-
127		-This page provides a brief introduction to Python syntax, Variables, Lists and Dicts, For loops and iterators, Functions, Classes, Importing modules, Writing and reading files with Pickling.
128		-=== [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] ===
129		-
130		-**Level**: advanced(%%) **Type**: user documentation
131		-
132		-NEURON's reaction-diffusion infrastructure can be used to readily allow intracellular concentrations to respond to currents generated in MOD files. This example shows you a simple model with just a single point soma, of length and diameter 10 microns, with Hodgkin-Huxley kinetics, and dynamic sodium (declared using rxd but without any additional kinetics).
133		-=== [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] ===
134		-
135		-**Level**: advanced(%%) **Type**: user documentation
136		-
137		-