Hong, NancyJasien, EmilyPagan, ChristopherXie, DanielCoulibaly, ZanaAdragni, Kofi P.Thorpe, Ian F.2018-09-252018-09-252014http://hdl.handle.net/11603/11385The study of allostery, a regulatory process that occurs in complex macromolecules such as proteins, is of particular interest as it has a key role in determining the function of these macromolecules. Allostery produces motional correlations that can be analyzed using different statistical methods. We implement a program in the statistical programming language R that uses polynomial regression and leave-one-out cross-validation to model relationships in data obtained from different sites in the protein, using the square root of the coefficient of determination to detect both linear and non-linear trends. The performance of the program will be studied on a simulated data set with linear and non-linear relationships and the effectiveness of the implemented methods as it relates to this problem will be assessed.7 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.UMBC High Performance Computing Facility (HPCF)allosterycomplex macromoleculesmotional correlations that can be analyzed using different statistical methodspolynomial regression and leave-one-out cross-validationmodel relationships in data obtained from different sites in the proteinText