Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS) |
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| Authors: | Jennifer M Staab Thomas M O'Connell Shawn M Gomez |
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| Affiliation: | (1) Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;(2) Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;(3) Division of Pharmacotherapy and Experimental Therapeutics, School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;(4) Hamner-UNC Center for Drug Safety Sciences, Research Triangle Park, North Carolina, USA;(5) Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, USA;(6) Joint Department of Biomedical Engineering, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA |
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| Abstract: | Background Nuclear magnetic resonance spectroscopy is one of the primary tools in metabolomics analyses, where it is used to track and quantify changes in metabolite concentrations or profiles in response to perturbation through disease, toxicants or drugs. The spectra generated through such analyses are typically confounded by noise of various types, obscuring the signals and hindering downstream statistical analysis. Such issues are becoming increasingly significant as greater numbers of large-scale systems or longitudinal studies are being performed, in which many spectra from different conditions need to be compared simultaneously. |
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