ReviewGenomics, proteomics & bioinformatics2013
Recent advances in computational methods for nuclear magnetic resonance data processing.
Review in Genomics, proteomics & bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Review
- Automation of peak-tracking analysis of stepwise perturbed NMR spectra.Journal of biomolecular NMR · 2017Article
- Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra.Scientific reports · 2015Article
- Progress and outlook in structural biology of large viral RNAs.Virus research · 2014Review
- An automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming.Journal of biomolecular NMR · 2014Article
- Bayesian peak picking for NMR spectra.Genomics, proteomics & bioinformatics · 2014Article
Corrections and comments
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Authors and funding
1 author.
Funding
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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.
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Registered trials
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