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Predicting β-Turns in Protein Using Kernel Logistic Regression
Joint Authors
Sheng, Yu
Elbashir, Murtada Khalafallah
Wang, Jianxin
Wu, Fang-Xiang
Li, Min
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-02-19
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
A β-turn is a secondary protein structure type that plays a significant role in protein configuration and function.
On average 25% of amino acids in protein structures are located in β-turns.
It is very important to develope an accurate and efficient method for β-turns prediction.
Most of the current successful β-turns prediction methods use support vector machines (SVMs) or neural networks (NNs).
The kernel logistic regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems.
However, it is often not found in β-turns classification, mainly because it is computationally expensive.
In this paper, we used KLR to obtain sparse β-turns prediction in short evolution time.
Secondary structure information and position-specific scoring matrices (PSSMs) are utilized as input features.
We achieved Qtotal of 80.7% and MCC of 50% on BT426 dataset.
These results show that KLR method with the right algorithm can yield performance equivalent to or even better than NNs and SVMs in β-turns prediction.
In addition, KLR yields probabilistic outcome and has a well-defined extension to multiclass case.
American Psychological Association (APA)
Elbashir, Murtada Khalafallah& Sheng, Yu& Wang, Jianxin& Wu, Fang-Xiang& Li, Min. 2013. Predicting β-Turns in Protein Using Kernel Logistic Regression. BioMed Research International،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1005315
Modern Language Association (MLA)
Elbashir, Murtada Khalafallah…[et al.]. Predicting β-Turns in Protein Using Kernel Logistic Regression. BioMed Research International No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1005315
American Medical Association (AMA)
Elbashir, Murtada Khalafallah& Sheng, Yu& Wang, Jianxin& Wu, Fang-Xiang& Li, Min. Predicting β-Turns in Protein Using Kernel Logistic Regression. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1005315
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1005315