Author: bugman
Date: Thu Jan 20 19:07:51 2011
New Revision: 12382
URL: http://svn.gna.org/viewcvs/relax?rev=12382&view=rev
Log:
Added my abstract and poster for ANZMAG 2004 - the first conference relax was
presented at.
This will appear at http://www.nmr-relax.com/events.html.
Added:
website/conferences/edward_abstract_ANZMAG_2004.txt (with props)
website/conferences/edward_poster_ANZMAG_2004.pdf (with props)
Added: website/conferences/edward_abstract_ANZMAG_2004.txt
URL:
http://svn.gna.org/viewcvs/relax/website/conferences/edward_abstract_ANZMAG_2004.txt?rev=12382&view=auto
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--- website/conferences/edward_abstract_ANZMAG_2004.txt (added)
+++ website/conferences/edward_abstract_ANZMAG_2004.txt Thu Jan 20 19:07:51
2011
@@ -1,0 +1,14 @@
+Fixing the model-free analysis of protein dynamics
+
+Edward d'Auvergne and Paul Gooley
+Russell Grimwade Department of Biochemistry, University of Melbourne, VIC,
3010 Australia.
+
+NMR is a powerful technique for the study of protein dynamics which can
reveal motional details on an atomic level. The NMR data commonly collected
includes the 15N R1 and R2 relaxation rates and the {1H}-15N steady-state
NOE. Model-free theory, the most widely used method for the analysis of this
relaxation data, permits the separation of pico to nanosecond motional
amplitudes (S2) and time-scales (?e). Model-free refers to the theory being
independent from a mechanical model of motion. Slower micro to millisecond
motions can be resolved by the extraction of chemical exchange relaxation
(Rex). Motions on two time-scales may also be extracted, when they occur,
using the parameters Sf2 and ?f for the faster motion and Ss2 and ?s for the
slower. Multiple mathematical models, usually five, can be constructed using
various combinations of these parameters. Model-free analysis consists of
fitting the model-free parameters to the collected relaxation data using
chi-squared minimisation. The data is fitted multiple times, once for each
model-free model, and the best of these models is selected.
+
+Two problems have been identified with the implementation of model-free data
analysis. The first is with the use of model selection, the second is with
minimisation. The current implementation of model-free model selection
consists of hypothesis testing using chi-squared and F-tests. It has been
found that this approach has two flaws, under-fitting, and not selecting a
model when one ought to be selected. The consequence is that the protein
falsely appears to be more rigid than reality. It was found that AIC model
selection, a standard and widely used statistical tool, increases the speed,
simplicity, and accuracy of model-free analysis (1).
+
+The second problem, due to the implementation of minimisation, results in
the extraction of incorrect parameter values. The program Modelfree is
almost universally used for model-free analysis and minimisation, however
other major programs include Dasha, DYNAMICS, and Tensor. A few of the
issues found in these programs include a programming bug, poor constraint
algorithms, minimisation terminating far too early, and poorly performing
minimisation algorithms. The effects include incorrect results effecting a
large proportion of the data, parameters stuck at the limits, inaccurate
parameter values, and minimisation not occuring. To solve these problems a
new program, relax, is currently under development. Both synthetic and real
data will be used to identify the best minimisation methods, to verify the
program, and to demonstrate the improvements over current analysis.
+
+
+References
+1. E. J. d'Auvergne and P. R. Gooley, Journal of Biomolecular NMR, 2003,
25, 25-39.
Propchange: website/conferences/edward_abstract_ANZMAG_2004.txt
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Added: website/conferences/edward_poster_ANZMAG_2004.pdf
URL:
http://svn.gna.org/viewcvs/relax/website/conferences/edward_poster_ANZMAG_2004.pdf?rev=12382&view=auto
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r12382 - in /website/conferences: edward_abstract_ANZMAG_2004.txt edward_poster_ANZMAG_2004.pdf