Author: bugman
Date: Fri Feb 5 19:58:02 2010
New Revision: 10671
URL: http://svn.gna.org/viewcvs/relax?rev=10671&view=rev
Log:
References pertaining to relax have been added to the info box container.
Each reference is a container placed within the 'bib' dictionary of the info
box class.
Modified:
1.3/info.py
Modified: 1.3/info.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/info.py?rev=10671&r1=10670&r2=10671&view=diff
==============================================================================
--- 1.3/info.py (original)
+++ 1.3/info.py Fri Feb 5 19:58:02 2010
@@ -70,6 +70,27 @@
if not dep_check.C_module_exp_fn:
self.errors.append(dep_check.C_module_exp_fn_mesg)
+ # References.
+ self._setup_references()
+
+
+ def _setup_references(self):
+ """Build a dictionary of all references useful for relax."""
+
+ # Initialise the dictionary.
+ self.bib = {}
+
+ # Place the containers into the dictionary.
+ self.bib['Clore90'] = Clore90()
+ self.bib['dAuvergne06'] = dAuvergne06()
+ self.bib['dAuvergneGooley03'] = dAuvergneGooley03()
+ self.bib['dAuvergneGooley06'] = dAuvergneGooley06()
+ self.bib['dAuvergneGooley07'] = dAuvergneGooley07()
+ self.bib['dAuvergneGooley08a'] = dAuvergneGooley08a()
+ self.bib['dAuvergneGooley08b'] = dAuvergneGooley08b()
+ self.bib['LipariSzabo82a'] = (LipariSzabo82a)
+ self.bib['LipariSzabo82b'] = (LipariSzabo82b)
+
def centre(self, string, width=100):
"""Format the string to be centred to a certain number of spaces.
@@ -90,3 +111,149 @@
# Return the new string.
return string
+
+
+
+class Clore90:
+ """Bibliography container."""
+
+ author = "Clore, G. M. and Szabo, A. and Bax, A. and Kay, L. E.
and Driscoll, P. C. and Gronenborn, A. M."
+ title = "Deviations from the simple 2-parameter model-free
approach to the interpretation of N-15 nuclear magnetic-relaxation of
proteins"
+ journal = "J. Am. Chem. Soc."
+ volume = "112"
+ number = "12"
+ pages = "4989-4991"
+ address = "1155 16th St, NW, Washington, DC 20036"
+ sourceid = "ISI:A1990DH27700070"
+ year = 1990
+
+
+
+class dAuvergne06:
+ """Bibliography container."""
+
+ author = "d'Auvergne, E. J."
+ title = "Protein dynamics: a study of the model-free analysis
of NMR relaxation data."
+ school = "Biochemistry and Molecular Biology, University of
Melbourne."
+ url =
"http://eprints.infodiv.unimelb.edu.au/archive/00002799/";
+ year = 2006
+
+
+
+class dAuvergneGooley03:
+ """Bibliography container."""
+
+ author = "d'Auvergne, E. J. and Gooley, P. R."
+ title = "The use of model selection in the model-free analysis
of protein dynamics."
+ journal = "J. Biomol. NMR"
+ volume = "25"
+ number = "1"
+ pages = "25-39"
+ abstract = "Model-free analysis of NMR relaxation data, which is
widely used for the study of protein dynamics, consists of the separation of
the global rotational diffusion from internal motions relative to the
diffusion frame and the description of these internal motions by amplitude
and timescale. Five model-free models exist, each of which describes a
different type of motion. Model-free analysis requires the selection of the
model which best describes the dynamics of the NH bond. It will be
demonstrated that the model selection technique currently used has two
significant flaws, under-fitting, and not selecting a model when one ought to
be selected. Under-fitting breaks the principle of parsimony causing bias in
the final model-free results, visible as an overestimation of S2 and an
underestimation of taue and Rex. As a consequence the protein falsely appears
to be more rigid than it actually is. Model selection has been extensively
developed in other fields. The techniques known as Akaike's Information
Criteria (AIC), small sample size corrected AIC (AICc), Bayesian Information
Criteria (BIC), bootstrap methods, and cross-validation will be compared to
the currently used technique. To analyse the variety of techniques, synthetic
noisy data covering all model-free motions was created. The data consists of
two types of three-dimensional grid, the Rex grids covering single motions
with chemical exchange [S2,taue,Rex], and the Double Motion grids covering
two internal motions [S f 2,S s 2,tau s ]. The conclusion of the comparison
is that for accurate model-free results, AIC model selection is essential. As
the method neither under, nor over-fits, AIC is the best tool for applying
Occam's razor and has the additional benefits of simplifying and speeding up
model-free analysis."
+ authoraddress = "Department of Biochemistry and Molecular Biology,
University of Melbourne, Melbourne, Victoria 3010, Australia.
ejdauv@xxxxxxxxxxxxxxxxxxxx"
+ keywords = "Amines ; Diffusion ; *Models, Molecular ; Motion ;
Nuclear Magnetic Resonance, Biomolecular/*methods ; Proteins/*chemistry ;
Research Support, Non-U.S. Gov't ; Rotation"
+ pubmed_id = 12566997
+ year = 2003
+
+
+
+class dAuvergneGooley06:
+ """Bibliography container."""
+
+ author = "d'Auvergne, E. J. and Gooley, P. R."
+ title = "Model-free model elimination: A new step in the
model-free dynamic analysis of NMR relaxation data."
+ journal = "J. Biomol. NMR"
+ volume = "35"
+ number = "2"
+ pages = "117-135"
+ abstract = "Model-free analysis is a technique commonly used
within the field of NMR spectroscopy to extract atomic resolution,
interpretable dynamic information on multiple timescales from the R (1), R
(2), and steady state NOE. Model-free approaches employ two disparate areas
of data analysis, the discipline of mathematical optimisation, specifically
the minimisation of a chi(2) function, and the statistical field of model
selection. By searching through a large number of model-free minimisations,
which were setup using synthetic relaxation data whereby the true underlying
dynamics is known, certain model-free models have been identified to, at
times, fail. This has been characterised as either the internal correlation
times, tau( e ), tau( f ), or tau( s ), or the global correlation time
parameter, local tau( m ), heading towards infinity, the result being that
the final parameter values are far from the true values. In a number of cases
the minimised chi(2) value of the failed model is significantly lower than
that of all other models and, hence, will be the model which is chosen by
model selection techniques. If these models are not removed prior to model
selection the final model-free results could be far from the truth. By
implementing a series of empirical rules involving inequalities these models
can be specifically isolated and removed. Model-free analysis should
therefore consist of three distinct steps: model-free minimisation,
model-free model elimination, and finally model-free model selection. Failure
has also been identified to affect the individual Monte Carlo simulations
used within error analysis. Each simulation involves an independent
randomised relaxation data set and model-free minimisation, thus simulations
suffer from exactly the same types of failure as model-free models.
Therefore, to prevent these outliers from causing a significant
overestimation of the errors the failed Monte Carlo simulations need to be
culled prior to calculating the parameter standard deviations."
+ authoraddress = "Department of Biochemistry and Molecular Biology,
Bio21 Institute of Biotechnology and Molecular Science, University of
Melbourne, Parkville, Victoria, 3010, Australia"
+ doi = "10.1007/s10858-006-9007-z"
+ pubmed_id = 16791734
+ year = 2006
+
+
+
+class dAuvergneGooley07:
+ """Bibliography container."""
+
+ author = "d'Auvergne, E. J. and Gooley, P. R."
+ title = "Set theory formulation of the model-free problem and
the diffusion seeded model-free paradigm."
+ journal = "Mol. Biosys."
+ volume = "3"
+ number = "7"
+ pages = "483-494"
+ abstract = "Model-free analysis of NMR relaxation data, which
describes the motion of individual atoms, is a problem intricately linked to
the Brownian rotational diffusion of the macromolecule. The diffusion tensor
parameters strongly influence the optimisation of the various model-free
models and the subsequent model selection between them. Finding the optimal
model of the dynamics of the system among the numerous diffusion and
model-free models is hence quite complex. Using set theory, the entirety of
this global problem has been encapsulated by the universal set Ll, and its
resolution mathematically formulated as the universal solution Ll. Ever since
the original Lipari and Szabo papers the model-free dynamics of a molecule
has most often been solved by initially estimating the diffusion tensor. The
model-free models which depend on the diffusion parameter values are then
optimised and the best model is chosen to represent the dynamics of the
residue. Finally, the global model of all diffusion and model-free parameters
is optimised. These steps are repeated until convergence. For simplicity this
approach to Ll will be labelled the diffusion seeded model-free paradigm.
Although this technique suffers from a number of problems many have been
solved. All aspects of the diffusion seeded paradigm and its consequences,
together with a few alternatives to the paradigm, will be reviewed through
the use of set notation."
+ authoraddress = "Department of Biochemistry and Molecular Biology,
Bio21 Institute of Biotechnology and Molecular Science, University of
Melbourne, Parkville, Melbourne, Victoria 3010, Australia."
+ keywords = "Magnetic Resonance Spectroscopy/*methods ; *Models,
Theoretical ; Proteins/chemistry ; Thermodynamics"
+ doi = "10.1039/b702202f"
+ pubmed_id = 17579774
+ year = 2007
+
+
+
+class dAuvergneGooley08a:
+ """Bibliography container."""
+
+ author = "d'Auvergne, E. J. and Gooley, P. R."
+ title = "Optimisation of NMR dynamic models I. Minimisation
algorithms and their performance within the model-free and Brownian
rotational diffusion spaces."
+ journal = "J Biomol NMR"
+ volume = "40"
+ number = "2"
+ pages = "107-119"
+ abstract = "The key to obtaining the model-free description of the
dynamics of a macromolecule is the optimisation of the model-free and
Brownian rotational diffusion parameters using the collected R (1), R (2) and
steady-state NOE relaxation data. The problem of optimising the chi-squared
value is often assumed to be trivial, however, the long chain of dependencies
required for its calculation complicates the model-free chi-squared space.
Convolutions are induced by the Lorentzian form of the spectral density
functions, the linear recombinations of certain spectral density values to
obtain the relaxation rates, the calculation of the NOE using the ratio of
two of these rates, and finally the quadratic form of the chi-squared
equation itself. Two major topological features of the model-free space
complicate optimisation. The first is a long, shallow valley which commences
at infinite correlation times and gradually approaches the minimum. The most
severe convolution occurs for motions on two timescales in which the minimum
is often located at the end of a long, deep, curved tunnel or
multidimensional valley through the space. A large number of optimisation
algorithms will be investigated and their performance compared to determine
which techniques are suitable for use in model-free analysis. Local
optimisation algorithms will be shown to be sufficient for minimisation not
only within the model-free space but also for the minimisation of the
Brownian rotational diffusion tensor. In addition the performance of the
programs Modelfree and Dasha are investigated. A number of model-free
optimisation failures were identified: the inability to slide along the
limits, the singular matrix failure of the Levenberg-Marquardt minimisation
algorithm, the low precision of both programs, and a bug in Modelfree.
Significantly, the singular matrix failure of the Levenberg-Marquardt
algorithm occurs when internal correlation times are undefined and is greatly
amplified in model-free analysis by both the grid search and constraint
algorithms. The program relax ( http://www.nmr-relax.com ) is also presented
as a new software package designed for the analysis of macromolecular
dynamics through the use of NMR relaxation data and which alleviates all of
the problems inherent within model-free analysis."
+ authoraddress = "Department of NMR-based Structural Biology, Max Planck
Institute for Biophysical Chemistry, Am Fassberg 11, D-37077, Goettingen,
Germany"
+ keywords = "*Algorithms ; Cytochromes c2/chemistry ; Diffusion ;
*Models, Molecular ; Nuclear Magnetic Resonance, Biomolecular/*methods ;
Rhodobacter capsulatus/chemistry ; *Rotation"
+ doi = "10.1007/s10858-007-9214-2"
+ pubmed_id = 18085410
+ year = 2008
+
+
+
+class dAuvergneGooley08b:
+ """Bibliography container."""
+
+ author = "d'Auvergne, E. J. and Gooley, P. R."
+ title = "Optimisation of NMR dynamic models II. A new
methodology for the dual optimisation of the model-free parameters and the
Brownian rotational diffusion tensor."
+ journal = "J Biomol NMR"
+ volume = "40"
+ number = "2"
+ pages = "121-133"
+ abstract = "Finding the dynamics of an entire macromolecule is a
complex problem as the model-free parameter values are intricately linked to
the Brownian rotational diffusion of the molecule, mathematically through the
autocorrelation function of the motion and statistically through model
selection. The solution to this problem was formulated using set theory as an
element of the universal set [formula: see text]-the union of all model-free
spaces (d'Auvergne EJ and Gooley PR (2007) Mol BioSyst 3(7), 483-494). The
current procedure commonly used to find the universal solution is to
initially estimate the diffusion tensor parameters, to optimise the
model-free parameters of numerous models, and then to choose the best model
via model selection. The global model is then optimised and the procedure
repeated until convergence. In this paper a new methodology is presented
which takes a different approach to this diffusion seeded model-free
paradigm. Rather than starting with the diffusion tensor this iterative
protocol begins by optimising the model-free parameters in the absence of any
global model parameters, selecting between all the model-free models, and
finally optimising the diffusion tensor. The new model-free optimisation
protocol will be validated using synthetic data from Schurr JM et al. (1994)
J Magn Reson B 105(3), 211-224 and the relaxation data of the
bacteriorhodopsin (1-36)BR fragment from Orekhov VY (1999) J Biomol NMR
14(4), 345-356. To demonstrate the importance of this new procedure the NMR
relaxation data of the Olfactory Marker Protein (OMP) of Gitti R et al.
(2005) Biochem 44(28), 9673-9679 is reanalysed. The result is that the
dynamics for certain secondary structural elements is very different from
those originally reported."
+ authoraddress = "Department of NMR-based Structural Biology, Max Planck
Institute for Biophysical Chemistry, Am Fassberg 11, Goettingen, D-37077,
Germany"
+ keywords = "Algorithms ; Amides/chemistry ;
Bacteriorhodopsins/chemistry ; Crystallography, X-Ray ; Diffusion ; *Models,
Molecular ; Nuclear Magnetic Resonance, Biomolecular/*methods ; Olfactory
Marker Protein/chemistry ; Peptide Fragments/chemistry ; Protein Structure,
Secondary ; *Rotation"
+ language = "eng"
+ doi = "10.1007/s10858-007-9213-3"
+ pubmed_id = 18085411
+ year = 2008
+
+
+
+class LipariSzabo82a:
+ """Bibliography container."""
+
+ author = "Lipari, G. and Szabo, A."
+ title = "Model-free approach to the interpretation of nuclear
magnetic-resonance relaxation in macromolecules I. Theory and range of
validity"
+ journal = "J. Am. Chem. Soc."
+ volume = "104"
+ number = "17"
+ pages = "4546-4559"
+ authoraddress = "NIADDKD,Chem Phys Lab,Bethesda,MD 20205."
+ sourceid = "ISI:A1982PC82900009"
+ year = 1982
+
+
+
+class LipariSzabo82b:
+ """Bibliography container."""
+
+ author = "Lipari, G. and Szabo, A."
+ title = "Model-free approach to the interpretation of nuclear
magnetic-resonance relaxation in macromolecules II. Analysis of experimental
results"
+ journal = "J. Am. Chem. Soc."
+ volume = "104"
+ number = "17"
+ pages = "4559-4570"
+ abstract = "For pt.I see ibid., vol.104, p.4546 (1982). In the
preceding paper it has been shown that the unique dynamic information on fast
internal motions in an NMR relaxation experiment on macromolecules in
solution is specified by a generalized order parameter, S , and an effective
correlation time, tau /sub e/. The authors now deal with the extraction and
interpretation of this information. The procedure used to obtain S /sup 2/
and tau /sub e/ from experimental data by using a least-squares method and,
in certain favorable circumstances, by using an analytical formula is
described. A variety of experiments are then analyzed to yield information on
the time scale and spatial restriction of internal motions of isoleucines in
myoglobin, methionines in dihydrofolate reductase and myoglobin, a number of
aliphatic residues in basic pancreatic trypsin inhibitor, and ethyl
isocyanide bound to myoglobin, hemoglobin, and aliphatic side chains in three
random-coil polymers. The numerical values of S /sup 2/ and tau /sub e / can
be readily interpreted within the framework of a variety of models."
+ authoraddress = "NIADDKD,Chem Phys Lab,Bethesda,MD 20205."
+ sourceid = "ISI:A1982PC82900010"
+ year = 1982
r10671 - /1.3/info.py