Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Optimal designs for Michaelis-Menten kinetic studies.

J N S Matthews1, G C Allcock

  • 1Department of Statistics, University of Newcastle, Newcastle upon Tyne NE1 7RU, U.K. j.n.s.matthews@ncl.ac.uk

Statistics in Medicine
|January 30, 2004
PubMed
Summary

This study optimizes substrate concentrations for estimating Michaelis-Menten parameters (K(M) and V(max)) using Bayesian D-optimal designs, considering various error distributions for accurate enzyme kinetics analysis.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Stepped wedge designs: insights from a design of experiments perspective.

Statistics in medicine·2017
Same author

Inconsistent treatment estimates from mis-specified logistic regression analyses of randomized trials.

Statistics in medicine·2015
Same author

Comparison of analgesic effects and patient tolerability of nabilone and dihydrocodeine for chronic neuropathic pain: randomised, crossover, double blind study.

BMJ (Clinical research ed.)·2008
Same author

Children's estimates of food portion size: the development and evaluation of three portion size assessment tools for use with children.

The British journal of nutrition·2007
Same author

Children's estimates of food portion size: the effect of timing of dietary interview on the accuracy of children's portion size estimates.

The British journal of nutrition·2007
Same author

Changes in consumption of sugars by English adolescents over 20 years.

Public health nutrition·2007

Area of Science:

  • Biochemistry and enzymology
  • Chemical kinetics
  • Statistical modeling

Background:

  • Enzyme kinetics are frequently described by the Michaelis-Menten equation.
  • Accurate estimation of Michaelis-Menten parameters (K(M) and V(max)) is crucial for characterizing enzyme reactions.
  • Current methods rely on observing reaction rates at various substrate concentrations.

Purpose of the Study:

  • To investigate optimal substrate concentration selection for parameter estimation in enzyme kinetics.
  • To determine Bayesian D-optimal designs for Michaelis-Menten models.
  • To explore designs focusing on alternative kinetic quantities and various error distributions.

Main Methods:

  • Utilized Bayesian D-optimal design principles.
  • Modeled enzyme kinetics using the Michaelis-Menten equation.

Related Experiment Videos

  • Assessed designs under normal distribution with constant variance and alternative error distributions.
  • Considered designs optimizing for K(M) or V(max)/K(M) ratio.

    • Main Results:

    • Identified optimal substrate concentration sets for accurate Michaelis-Menten parameter estimation.
    • Demonstrated the impact of different error distribution assumptions on optimal designs.
    • Showcased the utility of Bayesian D-optimal designs in experimental planning for enzymology.

    Conclusions:

    • Bayesian D-optimal designs provide an efficient strategy for selecting substrate concentrations in enzyme kinetics studies.
    • The choice of error distribution significantly influences the optimal experimental design.
    • These optimized designs enhance the precision of kinetic parameter estimates, including K(M) and V(max).