fitting with dynafit?

Dick Whitesell whiteselldick at
Fri Aug 10 18:08:04 EST 2001

I'm looking forward to using Gepasi, which has a very advanced help menu and
documentation. This sounds like a good site to get help from the Author
which you sure can't do with excel. I've been using the numerical
integration module from Numerical Recipes and finding global minima using
the kernel from Globals Unlimited. I have to tinker with stepsize in the
integration. To big winds up in a crash under certain conditions and too
small winds up taking too long.
 I am interested in detection of 13C glucose metabolites by NMR. Is there a
database that would give me the chemical shifts to expect for F6P?

"Pedro Mendes" <mendes at> wrote in message
news:9l0tmv$o4f$1 at
> At the risk of making some publicity to my own work:
> Least squares problems, especially with many data points and many
> variables, have many local minima in the error surface. This makes
> solving these problems with Levenberg-Marquardt (or other gradient
> descent methods) a challange. You need to be really close to the
> solution for these methods to converge. With the program GEPASI
> (which I am the author of), you can do the fitting with many different
> algorithms, including Levenberg-Marquardt . Importantly Gepasi contains
> Genetic Algoriths, Evolutionary programming and Multistart (with L-M)
> which all have a much bigger chance of solving your fitting problem.
> The only drawback to these methods is that they will take longer time
> to run.
> Gepasi is available for free at
> There is also a paper in the journal Bioinformatics discussing these
> (and optimisation in general):
> Mendes & Kell (1998) "Non-linear optimization of biochemical pathways:
> applications to metabolic engineering and parameter estimation."
> Bioinformatics, 4(10):869-83
> Abstract in PubMed:
> Disclaimer: I am the author of both the software and the paper that I
> mentioned above, so my opinion is definitly biased...
> --
> Pedro Mendes
> Assistant Research Professor
> Virginia Bioinformatics Institute
> Virginia Tech
> http:/

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