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Bayesian reconstruction of projection reconstruction NMR (PR-NMR)
- Authors
- Yoon, Ji Won
- Issue Date
- 1-Nov-2014
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Inverse problem; Projection reconstruction; Bayesian model selection; Reconstruction of multidimensional NMR spectra; Mixed linear model
- Citation
- COMPUTERS IN BIOLOGY AND MEDICINE, v.54, pp.89 - 99
- Indexed
- SCIE
SCOPUS
- Journal Title
- COMPUTERS IN BIOLOGY AND MEDICINE
- Volume
- 54
- Start Page
- 89
- End Page
- 99
- ISSN
- 0010-4825
- Abstract
- Projection reconstruction nuclear magnetic resonance (PR-NMR) is a technique for generating multidimensional NMR spectra. A small number of projections from lower-dimensional NMR spectra are used to reconstruct the multidimensional NMR spectra. In our previous work [1,2], it was shown that multidimensional NMR spectra are efficiently reconstructed using peak-by-peak based reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. We propose an extended and generalized RJMCMC algorithm replacing a simple linear model with a linear mixed model to reconstruct close NMR spectra into true spectra. This statistical method generates samples in a Bayesian scheme. Our proposed algorithm is tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA. (C) 2014 Elsevier Ltd. All rights reserved.
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- Yoon, Ji Won
- Department of Information Security