Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity

TURHAL, Uğur; Gök, Murat; DURGUT, Aykut

Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity

Uğur TURHAL, (Balıkesir Üniversitesi, Balıkesir, Türkiye)

Murat GÖK, (Yalova Üniversitesi, Yalova, Türkiye)

Aykut DURGUT (Balıkesir Üniversitesi, Balıkesir, Türkiye)

International Journal of Intelligent Systems and Applications in Engineering

0 0

Yıl: 2015 Cilt: 3 Sayı: 2 Sayfa Aralığı: 62 - 66 Metin Dili: İngilizce İndeks Tarihi: 29-07-2022

Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity

Öz:

HIV-1 protease which is responsible for the generation of infectious viral particles by cleaving the virus polypeptides, play an indispensable role in the life cycle of HIV-1. Knowledge of the substrate specificity of HIV-1 protease will pave the way of development of efficacious HIV-1 protease inhibitors. In the prediction of HIV-1 protease cleavage site techniques, many efforts have been devoted. Last decade, several works have approached the prediction of HIV-1 protease cleavage site problem by applying a number of methods from the field of machine learning. However, it is still difficult for researchers to choose the best method due to the lack of an effective and up-to-date comparison. Here, we have made an extensive study on feature encoding techniques for the problem of HIV-1 protease specificity on diverse machine learning algorithms. Also, for the first time, we applied OEDICHO technique, which is a combination of orthonormal encoding and the binary representation of selected 10 best physicochemical properties of amino acids derived from Amino Acid index database, to predict HIV-1 protease cleavage sites.

Anahtar Kelime:

Konular: Bilgisayar Bilimleri, Yapay Zeka

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

[1] Zachary Q. Beck, Laurence Hervio, Philip E. Dawson, John H. Elder and Edwin L. Madison (2000). Identification of Efficiently Cleaved Substrates for HIV-1 Protease Using a Phage Display Library and Use in Inhibitor Development. Virology. Vol. 274. Pages. 391- 401.
[2] You-Dong Cai and Kuo-Chen Chou (1998). Artificial Neural Network Model for Predicting HIV Protease Cleavage Sites in Protein. Advances in Engineering Software. Vol. 29. Pages. 119-128.
[3] Thomas B. Thompson, Kuo-Chen Chou and Chong Zheng (1995). Neural Network Prediction of the HIV-1 Protease Cleavage Sites. Journal of Theoretical Biology. Vol. 177. Pages. 369379.
[4] Yu-Dong Cai, Xiao-Jun Liu, Xue-Biao Xu and Kuo-Chen Chou (2002). Support Vector Machines for Predicting HIV Protease Cleavage Sites in Protein. Journal of Computational Chemistry. Vol. 23. Pages. 267-274.
[5] Thorsteinn Rognvaldsson and Liwen You (2004). Why Neural Networks Should Not Be Used For HIV-1 Protease Cleavage Site Prediction. Bioinformatics. Vol. 20. Pages. 1702-1709.
[6] Loris Nanni (2006). Comparison among Feature Extraction Methods for HIV-1 Protease Cleavage Site Prediction. Pattern Recognition. Vol. 39. Pages. 711-713.
[7] Aleksejs Kontijevskis, Jarl E. S. Wikberg and Jan Komorowski (2007). Computational Proteomics Analysis of HIV-1 Protease Interactome. Proteins: Structure, Function and Bioinformatics. Vol. 68. Pages. 305-312.
[8] Bing Niu, Lin Lu, Liang Liu, Tian H. Gu, Kai-Yan Feng, Wen-Cong Lu and Yu-Dong Cai (2009). HIV-1 Protease Cleavage Site Prediction Based on Amino Acid Property. Journal of Computational Chemistry. Vol. 30. Pages. 33- 39.
[9] Shuichi Kawashima and Minoru Kanehisa (2000). AAindex: Amino Acid Index Database. Nucleic Acids Research. Vol. 28. Page. 374. Available online: http://www.genome.jp/dbget/aaindex.html
[10] Jishou Ruan, Kui Wang, Jie Yang, Lukasz A. Kurgan and Krzysztof Cios (2005). Highly Accurate and Consistent Method for Prediction of Elix and Strand Content from Primary Protein Sequences. Artificial Intelligence in Medicine. Vol. 35. Pages. 19-35.
[11] Murat Gök and Ahmet T. Özcerit (2012). OETMAP: A New Feature Encoding Scheme for MHC Class I Binding Prediction. Molecular and Cellular Biochemistry. Vol. 359. Pages. 67-72.
[12] Murat Gök and Ahmet T. Özcerit (2012). Prediction of MHC Class I Binding Peptides with a New Feature Encoding Technique. Cellular Immunology. Vol. 275. Pages. 1-4.
[13] Alberto J. Perez-Jimenez and Juan C. Perez-Cortes (2006). Genetic Algorithms for Linear Feature Extraction. Pattern Recognition Letters. Vol. 27. Pages. 1508-1514.
[14] Israel Schechter and Arieh Berger (1967). On the Size of the Active Site in Proteases. I. Papain. Biochemical and Biophysical Research Communications. Vol. 27. Pages. 157-162.
[15] Pang-Ning Tan, Michael Steinbach and Vipin Kumar (2005). Introduction to Data Mining. Addison-Wesley Longman Publishing Co., Inc. Boston, ISBN: 0321321367.
[16] Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael Steinbach, David J. Hand and Dan Steinberg (2008). Top 10 Algorithms in Data Mining. Knowledge and Information Systems. Vol. 14. Pages. 1- 37.
[17] Du Zhang and Jeffrey J. P. Tsai (2007). Advances in Machine Learning Applications in Software Engineering. Idea Group Publishing. Page. 253.
[18] Christopher J.C. Burges (1998). A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery. Vol. 2. Pages. 121-167.
[19] David E. Rumelhart, Geoffrey E. Hinton and Ronald J. Williams (1986). Learning Internal Representations by Error Propagation. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Vol. 1. Pages. 318-362.
[20] Tom Fawcett (2004). ROC Graphs: Notes and Practical Considerations for Researchers. Technical Report, HP Laboratories. MS 1143. 1501 Page Mill Road. Palo Alto CA 94304. USA, 2004.
[21] Jin Huang and Charles X. Ling (2005). Using AUC and Accuracy in Evaluating Learning Algorithms. IEEE Transactions on Knowledge and Data Engineering. Vol. 17. Pages. 299-310.
[22] Arie Ben-David (2008). Comparison of Classification Accuracy Using Cohens Weighted Kappa. Expert Systems with Applications. Vol. 34. Pages. 825-832.
[23] Richard O. Duda, Peter E. Hart and David G. Stork (2000). Wiley. New York. ISBN: 978-0-471-05669-0.
[24] Thorsteinn Rögnvaldsson, Terence A. Etchells, Liwen You, Daniel Garwicz, Ian Jarman and Paulo J. G. Lisboa (2009). How to Find Simple and Accurate Rules for Viral Protease Cleavage Specificities. BMC Bioinformatics. Vol. 10. Page. 149.

APA	TURHAL U, Gök M, DURGUT A (2015). Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. , 62 - 66.
Chicago	TURHAL Uğur,Gök Murat,DURGUT Aykut Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. (2015): 62 - 66.
MLA	TURHAL Uğur,Gök Murat,DURGUT Aykut Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. , 2015, ss.62 - 66.
AMA	TURHAL U,Gök M,DURGUT A Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. . 2015; 62 - 66.
Vancouver	TURHAL U,Gök M,DURGUT A Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. . 2015; 62 - 66.
IEEE	TURHAL U,Gök M,DURGUT A "Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity." , ss.62 - 66, 2015.
ISNAD	TURHAL, Uğur vd. "Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity". (2015), 62-66.

APA	TURHAL U, Gök M, DURGUT A (2015). Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. International Journal of Intelligent Systems and Applications in Engineering, 3(2), 62 - 66.
Chicago	TURHAL Uğur,Gök Murat,DURGUT Aykut Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. International Journal of Intelligent Systems and Applications in Engineering 3, no.2 (2015): 62 - 66.
MLA	TURHAL Uğur,Gök Murat,DURGUT Aykut Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. International Journal of Intelligent Systems and Applications in Engineering, vol.3, no.2, 2015, ss.62 - 66.
AMA	TURHAL U,Gök M,DURGUT A Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. International Journal of Intelligent Systems and Applications in Engineering. 2015; 3(2): 62 - 66.
Vancouver	TURHAL U,Gök M,DURGUT A Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity. International Journal of Intelligent Systems and Applications in Engineering. 2015; 3(2): 62 - 66.
IEEE	TURHAL U,Gök M,DURGUT A "Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity." International Journal of Intelligent Systems and Applications in Engineering, 3, ss.62 - 66, 2015.
ISNAD	TURHAL, Uğur vd. "Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity". International Journal of Intelligent Systems and Applications in Engineering 3/2 (2015), 62-66.