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Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes
Joint Authors
Liu, Xiaoqing
Xu, Xinnan
Kong, Rui
He, Ping-an
Dai, Qi
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-18
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A human papillomavirus type plays an important role in the early diagnosis of cervical cancer.
Most of the prediction methods use protein sequence and structure information, but the reduced amino acid modes have not been used until now.
In this paper, we introduced the modes of reduced amino acids to predict high-risk HPV.
We first reduced 20 amino acids into several nonoverlapping groups and calculated their structure and physicochemical modes for high-risk HPV prediction, which was tested and compared with the existing methods on 68 samples of known HPV types.
The experiment result indicates that the proposed method achieved better performance with an accuracy of 96.49%, indicating that the reduced amino acid modes might be used to improve the prediction of high-risk HPV types.
American Psychological Association (APA)
Xu, Xinnan& Kong, Rui& Liu, Xiaoqing& He, Ping-an& Dai, Qi. 2020. Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1139469
Modern Language Association (MLA)
Xu, Xinnan…[et al.]. Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1139469
American Medical Association (AMA)
Xu, Xinnan& Kong, Rui& Liu, Xiaoqing& He, Ping-an& Dai, Qi. Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1139469
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139469