An online program can be found at
http://www.changbioscience.com/stat/ec50.html
Chang
Dr Engelbert Buxbaum <engelbert_buxbaum at hotmail.com> wrote in message news:<b03bo7$t56$04$1 at news.t-online.com>...
>adeboer at chem.vu.nl wrote:
>> > Hello,
> >
> > I am an analytical chemist, combining enzymes with analytical
> > instruments. Now I have a question.
> > If I will obtain Km and Vmax out of a michealis-menten plot, which type
> > of plot is the best to use, I mean: lineweaver-burk, eadie-hofstee,
> > hanes-woolf, direct linear...?
>> Transformation of data also transforms the measurement errors. For
> example in Lineweaver-Burk coordinates, error for the data with the
> smallest concentration becomes largest, at the same time these data
> points are shifted far to the right of the plot and influence the fit
> params particularly strong. As a result, fitted params (in particular
> Km) are off. Therefore, linearisation should be used only for
> presentation, not for fitting. Lineweaver-Burk is used most often for
> presentation and therefore easiest to interprete.
>> For actual data fitting non-linear regression to the untransformed data
> should be used. There are basically 2 algorithms available for this
> purpose: Marquard-Levenberg and Simplex. In their properties these are
> complementary: Simplex gives a better fit and is less sensitive to the
> choice of starting parameters, but can give error estimates for the
> parameters only by bootstrapping. Marquard-Levenberg gives error
> estimates directly, but does not work as well. Most computer packages
> use Marquard-Levenberg, for example Gnuplot or Sigma-Plot.
