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dc.contributor.authorGao, Xin
dc.date.accessioned2015-05-07T14:13:58Z
dc.date.available2015-05-07T14:13:58Z
dc.date.issued2013-01-11
dc.identifier.citationRecent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing 2013, 11 (1):29 Genomics, Proteomics & Bioinformatics
dc.identifier.issn16720229
dc.identifier.pmid23453016
dc.identifier.doi10.1016/j.gpb.2012.12.003
dc.identifier.urihttp://hdl.handle.net/10754/552477
dc.description.abstractAlthough 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.
dc.publisherElsevier BV
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1672022913000028
dc.rightsArchived with thanks to Genomics, Proteomics & Bioinformatics. http://creativecommons.org/licenses/by-nc-sa/3.0/
dc.subjectNuclear magnetic resonance
dc.subjectProtein structure
dc.subjectComputational methods
dc.subjectBioinformatics
dc.titleRecent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing
dc.typeArticle
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalGenomics, Proteomics & Bioinformatics
dc.identifier.pmcidPMC4357661
dc.eprint.versionPublisher's Version/PDF
kaust.personGao, Xin
refterms.dateFOA2018-06-13T09:36:47Z
dc.date.published-online2013-01-11
dc.date.published-print2013-02


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