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Abstract Details
Activity Number:
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575
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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ENAR
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Abstract - #306662 |
Title:
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A Goodness-of-Fit Test for the Protein Conformational Sampling
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Author(s):
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Mehdi Maadooliat*+ and Xin Gao and Jianhua Huang
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Companies:
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and King Abdullah University of Science and Technology and Texas A&M University
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Address:
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1001 Harvey Road, College Station, TX, 77840-3705, United States
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Keywords:
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protein structure prediction ;
protein backbone structure ;
principal components analysis ;
goodness of fit
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Abstract:
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Regardless of considerable progress in the past years, protein structure prediction remains as one of the major unsolved problems in computational biology. To predict protein structure, there has been much work on both template-based and template-free modeling methods, where each has its own advantages and disadvantages. Fragment assembly methods combine the advantages of the template-based and the template-free modeling to achieve more successful results in demonstrating the protein backbone structure.
The literature has focused on using variety of parametric models on sequential dependencies between the angle pairs along the protein chains. Despite the presence of different statistical methods for modeling the protein backbone structure, there is no statistical tool to evaluate the goodness of fit of such models. We propose to consider the joint distribution of the dihedral angles over different lags based on a nonparametric approach and monitor the behavior of the sequence of angles using the principal components analysis. As a result, we can develop graphical tools and numerical measurements to compare and evaluate the performance of different model fits.
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