Bayesian reconstruction of projection reconstruction NMR (PR-NMR)

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)89-99
Number of pages11
JournalComputers in Biology and Medicine
Volume54
DOIs
Publication statusPublished - 2014 Nov 1

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Markov Chains
Nuclear magnetic resonance
Linear Models
Markov processes
Magnetic Resonance Spectroscopy
Statistical methods
Proteins

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

Cite this

Bayesian reconstruction of projection reconstruction NMR (PR-NMR). / Yoon, Ji Won.

In: Computers in Biology and Medicine, Vol. 54, 01.11.2014, p. 89-99.

Research output: Contribution to journalArticle

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