Bayesian reconstruction of projection reconstruction NMR (PR-NMR)
DC Field | Value | Language |
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dc.contributor.author | Yoon, Ji Won | - |
dc.date.accessioned | 2021-09-05T03:07:40Z | - |
dc.date.available | 2021-09-05T03:07:40Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2014-11-01 | - |
dc.identifier.issn | 0010-4825 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/96811 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.subject | MAXIMUM-ENTROPY RECONSTRUCTION | - |
dc.subject | IMAGE-RECONSTRUCTION | - |
dc.subject | SPECTROSCOPY | - |
dc.title | Bayesian reconstruction of projection reconstruction NMR (PR-NMR) | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Yoon, Ji Won | - |
dc.identifier.doi | 10.1016/j.compbiomed.2014.08.016 | - |
dc.identifier.scopusid | 2-s2.0-84908294240 | - |
dc.identifier.wosid | 000345189800011 | - |
dc.identifier.bibliographicCitation | COMPUTERS IN BIOLOGY AND MEDICINE, v.54, pp.89 - 99 | - |
dc.relation.isPartOf | COMPUTERS IN BIOLOGY AND MEDICINE | - |
dc.citation.title | COMPUTERS IN BIOLOGY AND MEDICINE | - |
dc.citation.volume | 54 | - |
dc.citation.startPage | 89 | - |
dc.citation.endPage | 99 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Life Sciences & Biomedicine - Other Topics | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Biology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.subject.keywordPlus | MAXIMUM-ENTROPY RECONSTRUCTION | - |
dc.subject.keywordPlus | IMAGE-RECONSTRUCTION | - |
dc.subject.keywordPlus | SPECTROSCOPY | - |
dc.subject.keywordAuthor | Inverse problem | - |
dc.subject.keywordAuthor | Projection reconstruction | - |
dc.subject.keywordAuthor | Bayesian model selection | - |
dc.subject.keywordAuthor | Reconstruction of multidimensional NMR spectra | - |
dc.subject.keywordAuthor | Mixed linear model | - |
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