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.
2) Students write their own fitting code based on a PDF handout.
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!
If you'd like to use this assignment, please email me from your instructor account for access to the final code via GitHub.