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Activity Number:
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365
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #300671 |
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Title:
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Multidimensional Biomolecular NMR Studies: Noise Reduction and Component Identification
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Author(s):
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Nicoleta Serban*+
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Companies:
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Georgia Institute of Technology
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Address:
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765 Ferst Drive, NW, Atlanta, GA, 30318,
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Keywords:
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multi-dimensional NMR biomolecular studies ; multi-dimensional wavelet-based noise reduction ; multi-components identification
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Abstract:
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The overarching objective of the research presented at JSM is to shed light into the potential of wavelet-based methodology applied to data interpretation in NMR biomolecular studies. Specifically, the emphasis is on enhanced identification of spectral components in high-dimensional NMR frequency data using wavelet-based noise reduction. Our empirical investigation supports the benefits of initially reducing the noise for more detectable components and fewer false positives. The noise reduction method addresses a series of difficulties in NMR frequency data: local correlated noise, spatial heterogeneity and signal sparsity. The methodology is general, and therefore, it applies to other studies involving noise reduction of multidimensional data.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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