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Center of Excellence In Genomic Medicine Research
Document Details
Document Type
:
Article In Journal
Document Title
:
Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition
Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition
Document Language
:
English
Abstract
:
With the explosive growth of protein sequences entering into protein data banks in the post-genomic era, it is highly demanded to develop automated methods for rapidly and effectively identifying the protein–protein binding sites (PPBSs) based on the sequence information alone. To address this problem, we proposed a predictor called iPPBSPseAAC, in which each amino acid residue site of the proteins concerned was treated as a 15-tuple peptide segment generated by sliding a window along the protein chains with its center aligned with the target residue. The working peptide segment is further formulated by a general form of pseudo amino acid composition via the following procedures: (1) it is converted into a numerical series via the physicochemical properties of amino acids; (2) the numerical series is subsequently converted into a 20-D feature vector by means of the stationary wavelet transform technique. Formed by many individual “Random Forest” classifiers, the operation engine to run prediction is a two-layer ensemble classifier, with the 1st-layer voting out the best training data-set from many bootstrap systems and the 2nd-layer voting out the most relevant one from seven physicochemical properties. Cross-validation tests indicate that the new predictor is very promising, meaning that many important key features, which are deeply hidden in complicated protein sequences, can be extracted via the wavelets transform approach, quite consistent with the facts that many important biological functions of proteins can be elucidated with their low-frequency internal motions. The web server of iPPBS-PseAAC is accessible at http://www.jci-bioinfo.cn/iPPBS-PseAAC, by which users can easily acquire their desired results without the need to follow the complicated mathematical equations involved.
ISSN
:
0739-1102
Journal Name
:
Journal of Biomolecular Structure and Dynamics
Volume
:
34
Issue Number
:
9
Publishing Year
:
1437 AH
2016 AD
Article Type
:
Article
Added Date
:
Monday, July 10, 2017
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
Jia Jianhua
Jianhua, Jia
Researcher
Doctorate
Liu Zi
Zi, Liu
Researcher
Doctorate
Xiao Xuan
Xuan, Xiao
Investigator
Doctorate
Liu Bingxiang
Bingxiang, Liu
Researcher
Doctorate
Chou Kuo-Chen
Kuo-Chen, Chou
Researcher
Doctorate
Files
File Name
Type
Description
41928.pdf
pdf
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