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197	197	**Level**: advanced(%%) **Type**: user documentation
198	198
199	199	We will go over how to create an "unoptimized" model, set up a current clamp experiment on this model, configure a MultipleRunFitter to do a "run fitness" optimization, load the Experimental Data into the iclamp Run Fitness Generator, specify the parameters that will be adjusted and finally perform the optimization.
	200	+=== [[Reaction-Diffusion – Hodgkin-Huxley using rxd>>https://neuron.yale.edu/neuron/docs/hodgkin-huxley-using-rxd||rel=" noopener noreferrer" target="_blank"]] ===
200	200
	202	+**Level**: advanced(%%) **Type**: interactive tutorial
	203	+
	204	+In this tutorial you will learn how to set the proper parameters for the Hodgkin–Huxley model in NEURON.
	205	+=== [[Using the CellBuilder – Creating a stylised ("stick-figure") model cell>>https://neuron.yale.edu/neuron/static/docs/cbtut/stylized/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	206	+
	207	+**Level**: advanced(%%) **Type**: -
	208	+
	209	+Learn how to build an extremely simplified model of a pyramidal cell.
	210	+=== [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] ===
	211	+
	212	+**Level**: advanced(%%) **Type**: user documentation
	213	+
	214	+=== [[Reaction-Diffusion Example – Circadian rhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] ===
	215	+
	216	+**Level**: advanced(%%) **Type**: user documentation
	217	+
	218	+Here we develop a NEURON implementation of the Leloup-Goldbeter model for circadian rhythms in Drosophila. In this example NEURON's h library and its standard run system are being used as well as matplotlib to plot concentrations of circadian proteins over time.
	219	+=== [[Segmenting a simulation of a model cell – 3. Run a segmented simulation and save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results||rel=" noopener noreferrer" target="_blank"]] ===
	220	+
	221	+**Level**: advanced(%%) **Type**: user documentation
	222	+
	223	+=== [[ModelView: Compact display of parameters for NEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] ===
	224	+
	225	+**Level**: advanced(%%) **Type**: user documentation
	226	+
	227	+This example demonstrates how ModelView can explore a NEURON model.
	228	+=== [[Segmenting a simulation of a model network – 3. Run a segmented simulation and save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results-0||rel=" noopener noreferrer" target="_blank"]] ===
	229	+
	230	+**Level**: advanced(%%) **Type**: user documentation
	231	+
	232	+=== [[Segmenting a simulation of a model network – 4. Reconstitute and verify the "complete" simulation results>>https://neuron.yale.edu/neuron/docs/4-reconstitute-and-verify-complete-simulation-results-0||rel=" noopener noreferrer" target="_blank"]] ===
	233	+
	234	+**Level**: advanced(%%) **Type**: user documentation
	235	+
	236	+=== [[Using NEURON's Optimization Tools – Tutorial 1 : Fitting a function to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/func/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	237	+
	238	+**Level**: advanced(%%) **Type**: user documentation
	239	+
	240	+We will look into how to bring up a Multiple Run Fitter, load the Experimental Data into the Multiple Run Fitter, specify the function we want to optimize, specify the parameters that will be adjusted, specify the criteria we want the function to satisfy and finally perform the optimization.
	241	+=== [[Ball and Stick model part 4>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-4||rel=" noopener noreferrer" target="_blank"]] ===
	242	+
	243	+**Level**: advanced(%%) **Type**: user documentation
	244	+
	245	+=== [[Reaction-Diffusion>>https://neuron.yale.edu/neuron/docs/reaction-diffusion||rel=" noopener noreferrer" target="_blank"]] ===
	246	+
	247	+**Level**: advanced(%%) **Type**: interactive tutorial
	248	+
	249	+In this tutorial you will learn how to implement cell signalling function in the reaction-diffusion system by characterising your problems by the answers to three questions: (1) Where do the dynamics occur, (2) Who are the actors, and (3) How do they interact?
	250	+