Abstract
Classification for enzymes is essential for understanding the functions of organisms because it is directly related to the knowledge about which specific target it acts on, as well as to its catalytic process. Hence, it is crucial to use an accurate and robust approach to correctly map the enzyme in specific enzyme family class that it is belong to. In this research, a protein-protein interaction (PPI) network-based method was developed for predicting the families of enzyme. As a demonstration, the overall success rate by the jackknife test in identifying enzyme’s family class was 62.86%. The promising results imply that the predictor as presented in this paper may become a useful tool for studying enzymes.
Keywords: Amino acid frequency, enzyme family classes, jackknife test, PPI network-based method.
Graphical Abstract
Current Bioinformatics
Title:Prediction of Enzyme’s Family Based on Protein-Protein Interaction Network
Volume: 10 Issue: 1
Author(s): Bing Niu, Yin Lu, Jing Lu, Fuxue Chen, Tonghui Zhao, Zhanmin Liu, Tao Huang and Yuhui Zhang
Affiliation:
Keywords: Amino acid frequency, enzyme family classes, jackknife test, PPI network-based method.
Abstract: Classification for enzymes is essential for understanding the functions of organisms because it is directly related to the knowledge about which specific target it acts on, as well as to its catalytic process. Hence, it is crucial to use an accurate and robust approach to correctly map the enzyme in specific enzyme family class that it is belong to. In this research, a protein-protein interaction (PPI) network-based method was developed for predicting the families of enzyme. As a demonstration, the overall success rate by the jackknife test in identifying enzyme’s family class was 62.86%. The promising results imply that the predictor as presented in this paper may become a useful tool for studying enzymes.
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Cite this article as:
Niu Bing, Lu Yin, Lu Jing, Chen Fuxue, Zhao Tonghui, Liu Zhanmin, Huang Tao and Zhang Yuhui, Prediction of Enzyme’s Family Based on Protein-Protein Interaction Network, Current Bioinformatics 2015; 10 (1) . https://dx.doi.org/10.2174/157489361001150309122016
DOI https://dx.doi.org/10.2174/157489361001150309122016 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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