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Activity Number:
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446
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #300871 |
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Title:
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The Use of Singular Value Decomposition and Infrared Spectroscopy To Study Protein Folding Dynamics
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Author(s):
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Taylor Pressler*+
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Companies:
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Mount Holyoke College
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Address:
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, South Hadley, MA, 01075,
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Keywords:
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Spectroscopy ; Protein Misfolding ; Singular Value Decomposition ; Statistical Modeling ; Chemistry ; Time Series
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Abstract:
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Singular Value Decomposition (SVD) is a type of component analysis that can be used to decompose a real m x n matrix. SVD is very useful when analyzing large sets of spectroscopic data collected as a function of time. Infrared Spectroscopy is a technique which is widely used in biophysical chemistry research of the misfolding of proteins, which can be the underlying cause of many diseases. A time series of IR spectra is regarded as a matrix, in which each column corresponds to a spectra taken at a fixed time. A useful way to analyze the data is to decompose the matrix into a sum of terms by SVD. The individual terms in this decomposition then hold a real physical significance. Current research models for SVD and IR are examined and errors are found which ultimately lead to the over-interpretation of physical data.
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