1. An estimation method for enzyme kinetic model parameters based on Bayesian approach
Boseung Choi, Jae Kyoung Kim, and Grzegorz Rempala
Korea University Sejong Campus, Korea
Korea Advanced Institute of Science and Technology
The Ohio State University
OK. Thank you very much for this seminar. It is an honor to be here at MBI. My name is Boseng Choi. I came from Sejong, South Korea. You may hear the name of Seoul. It is capitol of Korea. Sejong is another new capital for government office. I hope Sejong city is similar to Washington D.C.
Today, I will talk about another reduced model for enzyme kinetics. I focus on the statistical estimation method for the enzyme kinetics model. I think that you have better information about enzyme kinetics. I started this research one and half year ago. Before the day, I never hear enzyme kinetics.
Jul
JSM 2018

2. Enzyme kinetics
Enzymes have been used as extremely specific catalysts in diverse industrial fields such as drug development, biofuel production, and food processing.
The enzyme kinetics is one of the fascinating areas of study in chemical kinetics and chemical reactions that are catalyzed by enzymes.
Enzymes are usually protein molecules that manipulate other molecules — the enzymes' substrates.

3. Example of enzyme kinetics
The initial substrate concentration is much larger than the enzyme.
The sum of enzyme and complex are same at all time point.
Complex reaches steady state quickly. C

4. Deterministic reduced model (sQSSA; sQ)
𝑘 𝑓 and 𝑘 𝑏 are not identifiable.
Reduction is essential to avoid the identifiability problem.

5. More accurate reduction (total QSSA; tQ)
Another reduced model is total quasi steady state model. This model developed later than sQSSA model and have little attention for parameter estimation.
tQSSA model use total substrate T. T is sum of substrate S and complex. We put this total substrate to the full model and solve this ODE for complex. And then we have new approximation model.

6. tQ model is accurate for all conditions

7. Gillespie algorithm (Kinetic Monte Carlo method)
One of the most widely used method is Gillespie algorithm. In this method, the macroscopic reaction rates in det systems are converted to propensity functions by changing the concentration to the number of molecules. This propensity functions describe the chance of certain reaction occurs.

8. Stochastic MM enzyme kinetics model

9. Contact information Boseung / )