Michaelis-Menten Fitting Code Project
This procedure walks students through writing a Python program that accepts enzyme activity data (substrate concentrations and associated velocities), fits the data to the Michaelis-Menten equation, and outputs a figure of the fit. Students should have a good understanding of Python before attempting this activity. The introductory tutorial linked below provides the necessary training students will need before attempting the project:
The Michaelis-Menten Fitting Code Project tutorial comes in two parts:
1) Students access a set of Jupyter Notebooks to walk through concepts in Michaelis-Menten kinetics, available via GitHub here.
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2) Students write their own fitting code based on a PDF handout.
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The tutorial is set up to work in ChemCompute, a free, online scientific computing environment maintained by Dr. Mark Perri at Sonoma State University. If you use ChemCompute, be sure to cite Dr. Perri!
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If you'd like to use this assignment, please email me from your instructor account for access to the final code via GitHub.