nD-PDPA
n-Dimensional Probability Density Profile Analysis
A. Fahim; S. Irausquin; H. Valafar Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, United States
Abstract
Structure characterization of a protein is expensive and time-consuming regardless of the novelty of the target protein. Probability density profile analysis (PDPA) has been previously introduced to directly address the economies of structure determination of routine proteins and subsequently, identification of novel structures from minimal sets of residual dipolar coupling (RDC) data. The 2D-PDPA, denoting incorporation of data from two alignment media, has been successful in identifying the structural homologue of an unknown ...
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