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

Inferring lifetime distributions from kinetics by maximizing entropy using a bootstrapped model.

Peter J Steinbach1

  • 1Center for Molecular Modeling, Center for Information Technology, National Institutes of Health, Building 12A Room 2051, 12 South Drive, Bethesda, Maryland 20892-5624, USA. steinbac@helix.nih.gov

Journal of Chemical Information and Computer Sciences
|November 26, 2002
PubMed
Summary

A new bootstrapped model refines lifetime distribution analysis from kinetic data, improving accuracy for overlapping phases. This method reduces artifacts and quantifies uncertainty in lifetime distribution, crucial for precise kinetic modeling.

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

Evidence for intrinsic DNA dynamics and deformability in damage sensing by the Rad4/XPC nucleotide excision repair complex.

Nucleic acids research·2025
Same author

Expanding the genetic and phenotypic landscape of replication factor C complex-related disorders: RFC4 deficiency is linked to a multisystemic disorder.

American journal of human genetics·2024
Same author

Concanavalin A Delivers a Photoactive Protein to the Bacterial Wall.

International journal of molecular sciences·2024
Same author

Bi-allelic SNAPC4 variants dysregulate global alternative splicing and lead to neuroregression and progressive spastic paraparesis.

American journal of human genetics·2023
Same author

Newly identified disorder of copper metabolism caused by variants in CTR1, a high-affinity copper transporter.

Human molecular genetics·2022
Same author

Modulation of free energy landscapes as a strategy for the design of antimicrobial peptides.

Journal of biological physics·2022

Area of Science:

  • Kinetics
  • Computational Modeling
  • Data Analysis

Background:

  • Analyzing kinetic data often involves complex lifetime distributions with overlapping exponential and distributed phases.
  • Traditional methods like maximum entropy can struggle with signal-to-noise limitations and regularization artifacts.

Purpose of the Study:

  • To develop a bootstrapped model to enhance the accuracy of lifetime distribution recovery from kinetic data.
  • To mitigate the over-smoothing of sharp features and under-smoothing of broad features common in regularization methods.

Main Methods:

  • A bootstrapped model is iteratively derived from the data, adjusting for low signal-to-noise ratios.
  • The model employs differential blurring to focus certain parts of the lifetime distribution while blurring others.

Related Experiment Videos

  • Uncertainty in the lifetime distribution is assessed by observing changes resulting from reasonable alterations to the default model.

    • Main Results:

    • The bootstrapped model produces lifetime distributions with significantly reduced artifacts.
    • The method improves the recovery of complex lifetime distributions involving overlapping and distributed phases.
    • The approach provides a reliable measure of uncertainty in the determined lifetime distribution.

    Conclusions:

    • The bootstrapped model offers a robust improvement over standard maximum entropy methods for kinetic lifetime analysis.
    • This technique is particularly valuable for analyzing data with low signal-to-noise ratios and complex phase behaviors.
    • The differential blurring and iterative refinement yield artifact-free distributions and reliable uncertainty estimations.