Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

Handle URI:
http://hdl.handle.net/10754/552477
Title:
Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing
Authors:
Gao, Xin ( 0000-0002-7108-3574 )
Abstract:
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing 2013, 11 (1):29 Genomics, Proteomics & Bioinformatics
Publisher:
Elsevier BV
Journal:
Genomics, Proteomics & Bioinformatics
Issue Date:
11-Jan-2013
DOI:
10.1016/j.gpb.2012.12.003
PubMed ID:
23453016
PubMed Central ID:
PMC4357661
Type:
Article
ISSN:
16720229
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S1672022913000028
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorGao, Xinen
dc.date.accessioned2015-05-07T14:13:58Zen
dc.date.available2015-05-07T14:13:58Zen
dc.date.issued2013-01-11en
dc.identifier.citationRecent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing 2013, 11 (1):29 Genomics, Proteomics & Bioinformaticsen
dc.identifier.issn16720229en
dc.identifier.pmid23453016en
dc.identifier.doi10.1016/j.gpb.2012.12.003en
dc.identifier.urihttp://hdl.handle.net/10754/552477en
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.en
dc.publisherElsevier BVen
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1672022913000028en
dc.rightsArchived with thanks to Genomics, Proteomics & Bioinformatics. http://creativecommons.org/licenses/by-nc-sa/3.0/en
dc.subjectNuclear magnetic resonanceen
dc.subjectProtein structureen
dc.subjectComputational methodsen
dc.subjectBioinformaticsen
dc.titleRecent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processingen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalGenomics, Proteomics & Bioinformaticsen
dc.identifier.pmcidPMC4357661en
dc.eprint.versionPublisher's Version/PDFen
kaust.authorGao, Xinen

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