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Bayesian estimation of Karplus parameters and torsion angles from three-bond scalar couplings constants

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons83949

Habeck,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Habeck, M., Rieping, W., & Nilges, M. (2005). Bayesian estimation of Karplus parameters and torsion angles from three-bond scalar couplings constants. Journal of Magnetic Resonance, 177(1), 160-165. Retrieved from http://www.bio.cam.ac.uk/zope/isd/publications/karplus_2005.pdf/view.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-D38F-0
Abstract
We apply Bayesian inference to analyze three-bond scalar coupling constants in an objective and consistent way. The Karplus curve and a Gaussian error law are used to model scalar coupling measurements. By applying Bayesamp;lsquo; theorem, we obtain a probability distribution for all unknowns, i.e., the torsion angles, the Karplus parameters, and the standard deviation of the Gaussian. We infer all these unknowns from scalar coupling data using Markov chain Monte Carlo sampling and analytically derive a probability distribution that only involves the torsion angles.