Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/82620
Title: Fourier-based classification of protein secondary structures
Authors: Shu, Jian-Jun
Yong, Kian Yan
Keywords: Classification
Protein secondary structures
Issue Date: 2017
Source: Shu, J. -J., & Yong, K. Y. (2017). Fourier-based classification of protein secondary structures. Biochemical and Biophysical Research Communications, 485(4), 731-735.
Series/Report no.: Biochemical and Biophysical Research Communications
Abstract: The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to classify protein secondary structures, but are faced with a significant number of misclassifications. The paper presents a technique for the classification of protein secondary structures based on protein “signal-plotting” and the use of the Fourier technique for digital signal processing. New indices are proposed to classify protein secondary structures by analyzing hydrophobicity profiles. The approach is simple and straightforward. Results show that the more types of protein secondary structures can be classified by means of these newly-proposed indices.
URI: https://hdl.handle.net/10356/82620
http://hdl.handle.net/10220/42344
ISSN: 0006-291X
DOI: 10.1016/j.bbrc.2017.02.117
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2017 Elsevier Inc. This is the author created version of a work that has been peer reviewed and accepted for publication by Biochemical and Biophysical Research Communications, Elsevier Inc. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.bbrc.2017.02.117].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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