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

Computational methods for diffusion-influenced biochemical reactions.

Maciej Dobrzynski1, Jordi Vidal Rodríguez, Jaap A Kaandorp

  • 1CWI (Center for Mathematics and Computer Science), Kruislaan 413 and Section Computational Science, Faculty of Science, University of Amsterdam, Kruislaan 403, Amsterdam, The Netherlands. m.dobrzynski@cwi.nl

Bioinformatics (Oxford, England)
|June 1, 2007
PubMed
Summary
This summary is machine-generated.

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

Correction: Walewicz et al. Effect of Radial Extracorporeal Shock Wave Therapy on Pain Intensity, Functional Efficiency, and Postural Control Parameters in Patients with Chronic Low Back Pain: A Randomized Clinical Trial. <i>J. Clin. Med.</i> 2020, <i>9</i>, 568.

Journal of clinical medicine·2026
Same author

Imaging-Guided Surgical Decision-Making and Bone Healing in Mandibular Cystic and Tumor-like Lesions: A Case-Based Radiologic Observation.

Diagnostics (Basel, Switzerland)·2026
Same author

Radiologic Evaluation of Odontogenic Sinusitis and Its Etiologic Factors: Lessons Learned from a Retrospective Study with a Proposed Imaging-Guided Management Pathway.

Journal of clinical medicine·2026
Same author

How Clinical and Radiological Findings in Chronic Mandibular Osteomyelitis Do Not Always Correlate: Diagnostic Dilemmas in Dental-Related Bone Inflammations.

Diagnostics (Basel, Switzerland)·2026
Same author

Biogenic Selenium Nanoparticles Functionalized with Natural Polymers or Phytochemicals for Targeted Disruption of <i>Candida</i> spp. Biofilms on Denture Materials: A Systematic Review.

Journal of functional biomaterials·2026
Same author

Hypericin-Mediated Antimicrobial Photodynamic Therapy in Dentistry: A Systematic Review of Applications Against Oral Biofilms and Infections.

Pharmaceutics·2026

Stochastic computational methods for biochemical systems yield different product fluctuations at low molecule numbers. Differences arise from how reaction event timing is modeled, impacting complex biological simulations.

Area of Science:

  • Biophysics
  • Computational Biology
  • Biochemistry

Background:

  • Stochastic computational methods are crucial for modeling biochemical systems.
  • Accurate simulation requires accounting for spatial and discrete reactant properties.
  • Existing methods include Brownian dynamics (BD) and the reaction-diffusion master equation.

Purpose of the Study:

  • To compare stochastic computational methods for biochemical systems.
  • To analyze the impact of spatial and discrete reactant considerations.
  • To evaluate method performance on gene expression and signal transduction models.

Main Methods:

  • Application of Brownian dynamics (BD) and reaction-diffusion master equation.
  • Simulation of a simplified gene expression model.

Related Experiment Videos

  • Analysis of a signal transduction pathway in Escherichia coli.

    • Main Results:

    • Methods show varying predicted fluctuations in product number for small molecule counts and diffusion-limited reactions.
    • Reaction-diffusion master equation results align with particle-based methods when sub-volume size approximates reactant diameter.
    • Discrepancies in fluctuation predictions stem from differing models of inter-arrival times between reaction events.

    Conclusions:

    • Computational approaches can yield different results in complex biological simulations due to modeling choices.
    • Understanding the physical assumptions behind mesoscopic models is essential.
    • Method selection impacts the accuracy of predicted molecular fluctuations.