A new feature encoding scheme for HIV-1 protease cleavage site prediction

Neural Computing and Applications

Volumn 22, Issue 7-8, 2013, Pages 1757-1761

  Gök, Murat ^a   Özcerit, Ahmet Turan ^b  

^a YALOVA UNIVERSITY   (Turkey)

^b SAKARYA UNIVERSITY   (Turkey)

Author keywords

Feature encoding scheme; Feature extraction; HIV 1 protease specificity; Peptide classification

Indexed keywords

CLASSIFICATION PERFORMANCE; ENCODING SCHEMES; ENCODING TECHNIQUES; HIV-1 PROTEASE; HIV-1 PROTEASE INHIBITORS; LINEAR SUPPORT VECTOR MACHINES; PEPTIDE CLASSIFICATION; SUBSTRATE SPECIFICITY;

AMINO ACIDS; ENCODING (SYMBOLS); FEATURE EXTRACTION; LEARNING ALGORITHMS; VIRUSES;

DISEASES;

EID: 84878554324     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-012-0967-5     Document Type: Article

References (16)

1. Chou KC (1996) Prediction of human immunodeficiency virus protease cleavage sites in proteins. Anal Biochem 233(1): 1-14.
2. Ding SF, Jia WK et al (2008) A survey on statistical pattern feature extraction. Adv Intell Comput Theor Appl Proc 5227: 701-708.
3. Duda RO, Hart PE, Stork DG (2001) Pattern classification, 2nd edn. John Wiley & Sons, New York.
4. Fawcett T (2004) ROC graphs: notes and practical considerations for researchers. Technical report, HP laboratories. Palo Alto, California.
5. Fukunaga K (1990) Introduction to statistical pattern recognition, 2nd edn. Academic Press, New York.
6. Guo J, YL Lin (2005) A novel method for protein subcellular localization: combining residue-couple model and SVM. Proceedings of the 3rd Asia-Pacific bioinformatics conference pp 117-129.
7. Henikoff S, Henikoff JG (1992) Amino-acid substitution matrices from protein blocks. Proc Natl Acad Sci USA 89(22): 10915-10919.
8. Kontijevskis A, Wikberg JE et al (2007) Computational proteomics analysis of HIV-1 protease interactome. Proteins-Struct Funct Bioinformatics 68(1): 305-312.
9. Maetschke S, Towsey M, Boden M (2005) Blomap: an encoding of amino acids which improves signal peptide cleavage prediction. Proceedings of the 3rd Asia-Pacific bioinformatics conference, pp 141-150.
10. Nanni L (2006) Comparison among feature extraction methods for HIV-1 protease cleavage site prediction. Pattern Recognit 39(4): 711-713.
11. Rognvaldsson T, You L (2004) Why neural networks should not be used for HIV-1 protease cleavage site prediction. Bioinformatics 20(11): 1702-1709.
12. Rognvaldsson T, Etchells TA et al (2009) How to find simple and accurate rules for viral protease cleavage specificities. BMC Bioinformatics 10: 149.
13. Schilling O, Overall CM (2008) Proteome-derived, database-searchable peptide libraries for identifying protease cleavage sites. Nat Biotechnol 26(6): 685-694.
14. Taylor WR (1986) The classification of amino-acid conservation. J Theor Biol 119(2): 205-218.
15. Wu C et al (1992) Protein classification artificial neural system. Protein Sci 1(5): 667-677.
16. Zvelebil MJ et al (1987) Prediction of protein secondary structure and active-sites using the alignment of homologous sequences. J Mol Biol 195(4): 957-961.