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Lucenz‐programmes for undergraduate analysis of enzyme kinetic data
Author(s) -
Clark Alan G.
Publication year - 2000
Publication title -
biochemistry and molecular biology education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.34
H-Index - 39
eISSN - 1539-3429
pISSN - 1470-8175
DOI - 10.1111/j.1539-3429.2000.tb00172.x
Subject(s) - sophistication , goodness of fit , selection (genetic algorithm) , yield (engineering) , computer science , linear regression , experimental data , regression analysis , simplicity , kinetic energy , statistics , mathematics , machine learning , physics , thermodynamics , sociology , social science , quantum mechanics
Two programmes for analysis of enzyme kinetic data are described. The programmes have evolved from use in undergraduate classes and accordingly the emphasis is on simplicity in design and use, rather than on computational sophistication. Data fitting, to a selection of predetermined models, proceeds via a weighted linear regression on to the reciprocals of the substrate concentrations and catalytic rates and is rapid and robust. The programmes yield best‐fit valus for K m , V m and, when appropriate, K i together with measures of the goodness of fit. Experimental data and lines of best fit may be presented graphically in up to seven diifferent plotting methods. Entered data and the graphical and numerical results of model fitting are displayed on the same screen so that relationships between all three may be readily appreciated. Variants of the programmes may be employed in the Windows 3 × or 9 × platforms or in DOS. © 2000 IUBMB. Published by Elsevier Science Ltd. All rights reserved.