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Solution of the Michaelis-Menten equation using the decomposition method
Author(s) -
Jagadeesh R. Sonnad,
Chetan T. Goudar
Publication year - 2008
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2009.6.173
Subject(s) - mathematics , michaelis–menten kinetics , decomposition , decomposition method (queueing theory) , computation , runge–kutta methods , differential equation , bisection method , algebraic number , interval (graph theory) , algebraic equation , mathematical analysis , chemistry , algorithm , physics , statistics , combinatorics , organic chemistry , nonlinear system , quantum mechanics , enzyme assay , enzyme
We present a low-order recursive solution to the Michaelis-Menten equation using the decomposition method. This solution is algebraic in nature and provides a simpler alternative to numerical approaches such as differential equation evaluation and root-solving techniques that are currently used to compute substrate concentration in the Michaelis-Menten equation. A detailed characterization of the errors in substrate concentrations computed from decomposition, Runge-Kutta, and bisection methods over a wide range of s(0) : K(m) values was made by comparing them with highly accurate solutions obtained using the Lambert W function. Our results indicated that solutions obtained from the decomposition method were usually more accurate than those from the corresponding classical Runge-Kutta methods. Moreover, these solutions required significantly fewer computations than the root-solving method. Specifically, when the stepsize was 0.1% of the total time interval, the computed substrate concentrations using the decomposition method were characterized by accuracies on the order of 10(-8) or better. The algebraic nature of the decomposition solution and its relatively high accuracy make this approach an attractive candidate for computing substrate concentration in the Michaelis-Menten equation.

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