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    Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

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    Description:
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    Type
    Article
    Authors
    Gao, Xin cc
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2013-01-11
    Online Publication Date
    2013-01-11
    Print Publication Date
    2013-02
    Permanent link to this record
    http://hdl.handle.net/10754/552477
    
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    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.
    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
    DOI
    10.1016/j.gpb.2012.12.003
    PubMed ID
    23453016
    PubMed Central ID
    PMC4357661
    Additional Links
    http://linkinghub.elsevier.com/retrieve/pii/S1672022913000028
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.gpb.2012.12.003
    Scopus Count
    Collections
    Articles; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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