Customer Reviews

Enzyme Kinetics: A Modern Approach

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The author has a view of how to analyse enzyme kinetic experiments that is very different from mine, but there are many who share his opinions, not mine, and many readers will find this an honourable and useful addition to the bookshelf. What the title means by "modern" is explained in the blurb: "With the advent of computers, linear transformations of models have become unnecessary -- Enzyme Kinetics does away with all linear transformations of enzyme kinetic models, advancing the use of nonlinear regression techniques." As I said, this view is not unique to the author, and those who share it will doubtless be glad to see the double-reciprocal plot and all the others consigned to the dustbin of history.

To me it is a case of throwing out the baby with the bath water. Yes, non-linear regression is a good step forward, but it needs to be applied with discretion, and it is dangerous to forget that even if computers are much better than humans at some tasks, they are worse at others. In particular, humans are much better than computers at noticing anomalies, but to do this they need something to look at, in other words a graph, and it is much easier to recognize an anomaly in the graph where the points ought to fall on a straight line than in one way they should fall on a curve.

If you do nonlinear analyses, you must also use residual graphs. They are much better than eyeballing whether a graph is linear or eyeballing if the data seem to fit a curve.

If you cannot do residual graphs, you should not use nonlinear analyses and stick with linear graphs, though even they are more dependable with the addition of a residual graph to check how well the data and equation fit. If you can do residuals, nonlinear analyses are faster, but not necessarily better in many cases. So, the reader should choose whether to use the author's method based on whether it is appropriate for their circumstances.