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Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing
Although three-dimensional protein structure determination using nuclear magnetic resonance (NMR) spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from specialists in bioinformatics and...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4357661/ https://www.ncbi.nlm.nih.gov/pubmed/23453016 http://dx.doi.org/10.1016/j.gpb.2012.12.003 |
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author | Gao, Xin |
author_facet | Gao, Xin |
author_sort | Gao, Xin |
collection | PubMed |
description | Although three-dimensional protein structure determination using nuclear magnetic resonance (NMR) spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing methods and outline some open problems in the field. We also discuss current trends in NMR technology development and suggest directions for research on future computational methods for NMR. |
format | Online Article Text |
id | pubmed-4357661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-43576612015-05-06 Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing Gao, Xin Genomics Proteomics Bioinformatics Review Although three-dimensional protein structure determination using nuclear magnetic resonance (NMR) spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing methods and outline some open problems in the field. We also discuss current trends in NMR technology development and suggest directions for research on future computational methods for NMR. Elsevier 2013-02 2013-01-11 /pmc/articles/PMC4357661/ /pubmed/23453016 http://dx.doi.org/10.1016/j.gpb.2012.12.003 Text en © 2013 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Published by Elsevier Ltd and Science Press. All rights reserved. http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/). |
spellingShingle | Review Gao, Xin Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing |
title | Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing |
title_full | Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing |
title_fullStr | Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing |
title_full_unstemmed | Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing |
title_short | Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing |
title_sort | recent advances in computational methods for nuclear magnetic resonance data processing |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4357661/ https://www.ncbi.nlm.nih.gov/pubmed/23453016 http://dx.doi.org/10.1016/j.gpb.2012.12.003 |
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