Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples.
Although NMR spectroscopic techniques coupled with multivariate statistics can yield much useful information for classifying biological samples based on metabolic profiles, biomarker identification remains a time-consuming and complex procedure involving separation methods, two-dimensional NMR, and...
| Main Authors: | , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2007
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| _version_ | 1797057248888881152 |
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| author | Smith, L Maher, A Cloarec, O Rantalainen, M Tang, H Elliott, P Stamler, J Lindon, J Holmes, E Nicholson, J |
| author_facet | Smith, L Maher, A Cloarec, O Rantalainen, M Tang, H Elliott, P Stamler, J Lindon, J Holmes, E Nicholson, J |
| author_sort | Smith, L |
| collection | OXFORD |
| description | Although NMR spectroscopic techniques coupled with multivariate statistics can yield much useful information for classifying biological samples based on metabolic profiles, biomarker identification remains a time-consuming and complex procedure involving separation methods, two-dimensional NMR, and other spectroscopic tools. We present a new approach to aid complex biomixture analysis that combines diffusion ordered (DO) NMR spectroscopy with statistical total correlation spectroscopy (STOCSY) and demonstrate its application in the characterization of urinary biomarkers and enhanced information recovery from plasma NMR spectra. This method relies on calculation and display of the covariance of signal intensities from the various nuclei on the same molecule across a series of spectra collected under different pulsed field gradient conditions that differentially attenuate the signal intensities according to translational molecular diffusion rates. We term this statistical diffusion-ordered spectroscopy (S-DOSY). We also have developed a new visualization tool in which the apparent diffusion coefficients from DO spectra are projected onto a 1D NMR spectrum (diffusion-ordered projection spectroscopy, DOPY). Both methods either alone or in combination have the potential for general applications to any complex mixture analysis where the sample contains compounds with a range of diffusion coefficients. |
| first_indexed | 2024-03-06T19:33:35Z |
| format | Journal article |
| id | oxford-uuid:1e4c6dc1-9eec-4dc4-80c3-2508a58a0e63 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:33:35Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | oxford-uuid:1e4c6dc1-9eec-4dc4-80c3-2508a58a0e632022-03-26T11:15:31ZStatistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1e4c6dc1-9eec-4dc4-80c3-2508a58a0e63EnglishSymplectic Elements at Oxford2007Smith, LMaher, ACloarec, ORantalainen, MTang, HElliott, PStamler, JLindon, JHolmes, ENicholson, JAlthough NMR spectroscopic techniques coupled with multivariate statistics can yield much useful information for classifying biological samples based on metabolic profiles, biomarker identification remains a time-consuming and complex procedure involving separation methods, two-dimensional NMR, and other spectroscopic tools. We present a new approach to aid complex biomixture analysis that combines diffusion ordered (DO) NMR spectroscopy with statistical total correlation spectroscopy (STOCSY) and demonstrate its application in the characterization of urinary biomarkers and enhanced information recovery from plasma NMR spectra. This method relies on calculation and display of the covariance of signal intensities from the various nuclei on the same molecule across a series of spectra collected under different pulsed field gradient conditions that differentially attenuate the signal intensities according to translational molecular diffusion rates. We term this statistical diffusion-ordered spectroscopy (S-DOSY). We also have developed a new visualization tool in which the apparent diffusion coefficients from DO spectra are projected onto a 1D NMR spectrum (diffusion-ordered projection spectroscopy, DOPY). Both methods either alone or in combination have the potential for general applications to any complex mixture analysis where the sample contains compounds with a range of diffusion coefficients. |
| spellingShingle | Smith, L Maher, A Cloarec, O Rantalainen, M Tang, H Elliott, P Stamler, J Lindon, J Holmes, E Nicholson, J Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. |
| title | Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. |
| title_full | Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. |
| title_fullStr | Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. |
| title_full_unstemmed | Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. |
| title_short | Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. |
| title_sort | statistical correlation and projection methods for improved information recovery from diffusion edited nmr spectra of biological samples |
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