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 Concept Videos

Measuring Reaction Rates03:09

Measuring Reaction Rates

25.3K
Polarimetry finds application in chemical kinetics to measure the concentration and reaction kinetics of optically active substances during a chemical reaction. Optically active substances have the capability of rotating the plane of polarization of linearly polarized light passing through them—a feature called optical rotation. Optical activity is attributed to the molecular structure of substances. Normal monochromatic light is unpolarized and possesses oscillations of the electrical...
25.3K
Reaction Rate02:53

Reaction Rate

52.5K
The rate of reaction is the change in the amount of a reactant or product per unit time. Reaction rates are therefore determined by measuring the time dependence of some property that can be related to reactant or product amounts. Rates of reactions that consume or produce gaseous substances, for example, are conveniently determined by measuring changes in volume or pressure.
The mathematical representation of the change in the concentration of reactants and products, over time, is the rate...
52.5K
Multi-Step Reactions02:31

Multi-Step Reactions

7.3K
Chemical reactions often occur in a stepwise fashion involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs. Each of the steps in a reaction mechanism is called an elementary reaction. These...
7.3K
The Integrated Rate Law: The Dependence of Concentration on Time02:39

The Integrated Rate Law: The Dependence of Concentration on Time

35.3K
While the differential rate law relates the rate and concentrations of reactants, a second form of rate law called the integrated rate law relates concentrations of reactants and time. Integrated rate laws can be used to determine the amount of reactant or product present after a period of time or to estimate the time required for a reaction to proceed to a certain extent. For example, an integrated rate law helps determine the length of time a radioactive material must be stored for its...
35.3K
Fundamental Mathematical Principles in Pharmacokinetics: Rate and Order of Reaction01:15

Fundamental Mathematical Principles in Pharmacokinetics: Rate and Order of Reaction

432
In pharmacokinetics, the rates and order of reactions play a crucial role in understanding how the body processes drugs and help us comprehend drug absorption, distribution, metabolism, and elimination. A critical concept in pharmacokinetics is the rate constant, which quantifies the speed of a reaction. It provides valuable information about the kinetics of drug elimination. The rate constant allows us to determine the rate at which drugs are eliminated from the body.
Pharmacokinetic reactions...
432
Determining Order of Reaction02:53

Determining Order of Reaction

55.9K
Rate laws describe the relationship between the rate of a chemical reaction and the concentration of its reactants. In a rate law, the rate constant k and the reaction orders are determined experimentally by observing how the rate of reaction changes as the concentrations of the reactants are changed. A common experimental approach to the determination of rate laws is the method of initial rates. This method involves measuring reaction rates for multiple experimental trials carried out using...
55.9K

You might also read

Related Articles

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

Sort by
Same author

Read-Across Structural Analysis of PFAS Acute Oral Toxicity in Rats Powered by the Isalos Analytics Platform's Automated Machine Learning.

Toxics·2026
Same author

Alchemical space exploration in drug design <i>via</i> stochastic expanding boundary optimization search.

Physical chemistry chemical physics : PCCP·2026
Same author

Kinetic rate of methane hydrate film growth from microsecond molecular dynamics simulations.

The Journal of chemical physics·2025
Same author

Multi-scale study of cobalt adsorption on TiO2 anatase (101): From DFT to force-field parameterization.

The Journal of chemical physics·2025
Same author

Assessment of the Binding Patterns for Endocrine Disrupting Chemicals in Complex with Estrogen and Androgen Receptors by Leveraging the Asclepios Enalos KNIME Nodes.

Journal of chemical information and modeling·2025
Same author

A Systematic Literature Review of Reproductive Toxicological Studies on Phthalates.

International journal of molecular sciences·2025

Related Experiment Video

Updated: Jul 13, 2025

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
09:42

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Published on: January 16, 2016

9.1K

Statistical Inference of Rate Constants in Chemical and Biochemical Reaction Networks Using an "Inverse" Event-Driven

Ioannis G Diamataris1, Loukas D Peristeras2, Konstantinos D Papavasileiou3,4,5

  • 1Laboratory of Computational Physical-Chemistry, Department of Molecular Biology and Genetics, University of Thrace, Alexandroupoulis GR-681 00, Greece.

The Journal of Physical Chemistry. B
|October 12, 2023
PubMed
Summary

This study introduces a new algorithm to derive kinetic parameters for stochastic reaction networks. The method accurately estimates rate constants from time-evolution data, aiding in understanding molecular processes.

More Related Videos

Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions
13:00

Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions

Published on: April 4, 2014

20.7K
Steady-state, Pre-steady-state, and Single-turnover Kinetic Measurement for DNA Glycosylase Activity
14:27

Steady-state, Pre-steady-state, and Single-turnover Kinetic Measurement for DNA Glycosylase Activity

Published on: August 19, 2013

19.4K

Related Experiment Videos

Last Updated: Jul 13, 2025

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
09:42

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Published on: January 16, 2016

9.1K
Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions
13:00

Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions

Published on: April 4, 2014

20.7K
Steady-state, Pre-steady-state, and Single-turnover Kinetic Measurement for DNA Glycosylase Activity
14:27

Steady-state, Pre-steady-state, and Single-turnover Kinetic Measurement for DNA Glycosylase Activity

Published on: August 19, 2013

19.4K

Area of Science:

  • Chemical Kinetics
  • Computational Biology
  • Systems Biology

Background:

  • Stochastic reaction networks are crucial for understanding finite reactive systems.
  • Deriving kinetic parameters for stochastic kinetics is a significant challenge.

Purpose of the Study:

  • To develop a novel algorithm for inferring kinetic parameters from system time evolution.
  • To reconstruct distributions for parameter estimation in stochastic processes.

Main Methods:

  • Algorithm infers kinetic parameters from changes in molecular species populations over time.
  • Method reconstructs necessary distributions for parameter inference.
  • Validated using event-driven Monte Carlo (MC) simulations with the Gillespie algorithm.

Main Results:

  • Accurately replicates rate constants for stochastic reaction networks.
  • Successfully estimates association and dissociation rate constants from molecular dynamics (MD) simulations.

Conclusions:

  • The developed method simplifies kinetic parameter derivation for stochastic systems.
  • Offers a valuable tool for linking macroscopic properties to molecular events in physical and biological processes.