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dc.contributor.authorKeyvanloo Shahrestanaky, Amirmohamad.en_US
dc.date.accessioned2009-06-29T14:36:51Z
dc.date.available2009-06-29T14:36:51Z
dc.date.issued2004-06-29T14:36:51Z
dc.identifier.urihttp://hdl.handle.net/10464/1643
dc.description.abstractSolid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectNuclear magnetic resonance spectroscopy.en_US
dc.subjectInversion (Geophysics)en_US
dc.subjectAmyloid beta-proteinen_US
dc.titleExtracting Ramachandran torsional angle distributions from 2D NMR data using Tikhonov regularization /en_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.Sc. Physicsen_US
dc.degree.levelMastersen_US
dc.contributor.departmentDepartment of Physicsen_US
dc.degree.disciplineFaculty of Mathematics and Scienceen_US


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