Kinetic Methods of Analysis: How Do They Rate?

Crouch, S. R.

doi:10.1002/jccs.199400034

Cited by 5 publications

(1 citation statement)

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“…[9][10][11][12][13][14][15][16][17][18][19][20] Responses of biological networks to various stimulants and perturbations can be calculated, given network structure, parameters, and initial conditions. [21][22][23][24][25] However, parameter sets are rarely available. Given a network topology, the compositional response can be deduced from an analytical expression of a solution to the ordinary differential equation (ODE) of the system.…”

Section: Introductionmentioning

confidence: 99%

Noise response in monomolecular closed systems

Fajiculay

Hsu

2023

J Chinese Chemical Soc

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One of the primary interests in understanding biological systems is the interaction between noise and cellular regulation. Noise levels can be altered by rate constant perturbations, which may result in an imbalance of important biological functions. Although the theory of noise localization can estimate noise perturbation response, it is currently limited to open systems, where the majority of biological networks belong. However, during their lifetime, some components of biological systems participate in reactions that can be categorized under a closed system. Therefore, a counterpart theory for closed systems is desirable. In this work, steady‐state perturbations of monomolecular closed systems and ways to estimate the response of noise as (co)variances are explored. We extend the structural sensitivity analysis for analyzing noise response patterns by using additional clues derived from multinomial assumptions. We identified scenarios in which this combination might fail in noise prediction, which we call noise flip, arising from the nonlinear dependence of variance upon composition. Nevertheless, theoretical intuition and simulation show that noise flip diminishes with increasing system size. This work provides an efficient and scalable means to estimate noise responses with potential applications in model discrimination, network‐wide response scanning, and reconstruction.

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Section: Introductionmentioning

confidence: 99%

Noise response in monomolecular closed systems

Fajiculay

Hsu

2023

J Chinese Chemical Soc

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Instrumentation for Kinetics

Cordos

2000

Encyclopedia of Analytical Chemistry

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In kinetic methods or reaction‐rate methods of analysis, the rate of a given reaction is measured and related to the concentration of the sought‐for species. The instrumentation in kinetics is primarily designed to monitor the evolution of the analytical signal with time. Unlike in the traditional equilibrium‐based approaches, where the signal is measured after the reaction has reached completion, in kinetic methods the signal is usually measured in the first few percent of the total reaction time. Therefore, the advantages and limitations of kinetic methods should be considered in their relations with equilibrium methods. Kinetic methods are faster than equilibrium‐based methods since the user does not have to wait for a reaction to go to completion. They are relative methods that depend on changes in concentration and not on its absolute value and they could be more selective than equilibrium methods since the difference between reaction constants could be used to discriminate against an interfering species. The limitations of kinetic methods are a lower precision and a strong dependence on experimental conditions. The main factors that cause these limitations are the measured signal, which is small in comparison with that from an equilibrium reaction, and the dependence of rate constants on temperature, pH, ionic strength, etc. Therefore, the measurement systems used in kinetic methods should be sensitive and the experimental conditions should be kept strictly constant. The best results in kinetic methods are obtained with instrumental systems having a high degree of automation. The main operations that should be carried out by the instrumentation in kinetic determinations are the mixing of the reactants, measurement of the detector signal in time and processing of data to obtain the reaction rate and concentration. The mixing of the reactants should be done in a time shorter than the reaction half‐life and it is critical for fast reactions where required mixing times are of the order of milliseconds. In these cases the mixing is accomplished by mechanical systems that rapidly drive the reactants through a mixing chamber into an observation chamber. For slower reaction the best mixing procedures are based on automated flow analyzers that have different manifolds configurations adapted both to sample processing and to reactant mixing. After mixing, the reaction could be monitored in time either by stopping the flow and recording the signal or by passing the reacting plug several times through the detector and reading the signal after each pass. The measurement of the detector signal, after the reagents are mixed, could be done with a large variety of detectors, but the most commonly used detection systems are photometric and electrochemical. Photometric detection provides a short response time, specificity and the possibility of collecting full spectra very rapidly if photodetector arrays are used. Electrochemical detectors are simple and relatively inexpensive. The concentration of the analyte is determined from the slope of the detector signal. In many routine procedures the slope is determined by measuring the signal at one or two fixed points in time or by determining the time required by the signal to reach a predetermined level. These procedures have the advantage that they are rapid and need no supplementary instrumentation for data processing. Another approach in kinetic data processing, based on computer software, computes a curve that fits the experimental data. The slope or concentration is then extracted from the mathematical expression of the fitting curve.

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