That is extremely useful information, thanks!

Jeremy Anderson

Ph.D. Candidate

Johns Hopkins University
Program in Molecular Biophysics
Laboratory of Dr. Vincent J. Hilser, Ph.D.
3400 N Charles St, 104 Mudd Hall
Baltimore, MD 21218

(Lab) *410-516-6757*
(Cell) 715-613-0274

On Tue, Nov 15, 2016 at 8:49 AM, Edward d'Auvergne <>

> On 15 November 2016 at 14:33, Jeremy Anderson <> wrote:
> > Hi Edward,
> >
> > Thanks for the follow up.  I totally understand the reasons for not
> having
> > fixed values within a relax analysis, it seems like a special case
> relative
> > to what I've seen in the literature and increases ones ability to skew
> the
> > results to their liking, I'm doing my best to safeguard against that
> myself.
> No problems.  You do have to be quite careful, as it is far too easy
> to fall into an alternative reality that can nicely explain some of
> the biology.  Mapping the optimisation space is an essential tool when
> constraining certain parameters to see if you are at a well defined
> minimum.  For example it can show you if you've just chopped across a
> valley in the space and the optimiser is landing at the bottom of that
> valley where it has been cut.  If you have access to the ancient, yet
> very powerful OpenDX software, you can use the and dx.execute
> relax user functions for this.
> > I was able to implement such an analysis in python using the RD models
> from
> > relax as well as the scipy and lmfit packages to both hold the dw
> parameters
> > constant while performing the usual grid search then nonlinear least
> squares
> > minimization and perform a cluster analysis holding the rate constant
> and/or
> > the major population constant amongst all residues.  The code is a bit
> of a
> > mess at the moment but I'm hoping to clean it up and make a repository on
> > github, so I can better document what I did and so other folks can check
> it
> > out if they want.
> Note that I originally looked at the scipy optimisation packages for
> relax.  However I found fatal bugs in all three of the algorithms
> implemented at the time (Levenberg-Marquardt being one of them).  The
> algorithms appeared to minimise the results, but they were nothing
> like what Art Palmer's Modelfree4 found.  I was comparing relax to
> Modelfree4 for debugging at the time when implementing the model-free
> analysis component.  I don't know if anything has changed since then,
> but you really need to be wary and double check whenever you use any
> part of scipy.  Anyway, because scipy's optimisation was so terrible,
> I decided to write the minfx optimisation library
> (  You'll see a record of all of this
> in my publication history ;)
> > Thanks for your assistance.
> You're welcome!
> Regards,
> Edward
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