Comparison among feature extraction methods for HIV-1 protease cleavage site prediction

Pattern Recognition

Volumn 39, Issue 4, 2006, Pages 711-713

  Nanni, Loris ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Feature extraction; Fusion of classifiers; HIV 1 protease

Indexed keywords

ENZYMES; ERROR CORRECTION; LEARNING SYSTEMS; PROBLEM SOLVING;

FEATURE SPACES; FUSION OF CLASSIFIERS; HIV-1 PROTEASE; PROTEASE SPECIFICITY PROBLEM;

FEATURE EXTRACTION;

EID: 32044474813     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2005.11.002     Document Type: Article

References (5)

1. T. Rögnvaldsson, L. You, Why neural networks should not be used for HIV-1 protease cleavage site prediction, Bioinformatics (2003) 1702-1709.
2. L.I. Kuncheva, and C.J. Whitaker Ten measures of diversity in classifier ensembles: limits for two classifiers, IEEE Workshop on International Sensor Processing February 2001 Birmingham
3. C.H. Wu, G. Whitson, J. McLarty, A. Ermongkonchai, and T.C. Change PROCANS: protein classification artificial neural system Protein Sci. 1 1 1992 667 677
4. J. Ruan, K. Wang, J. Yang, L.A. Kurgan, K. Cios, Highly accurate and consistent method for prediction of elix and strand content from primary protein sequences, Artif. Intell. (2005) (Medicine on-line version).
5. J. Guo, Y. Lin, Z. Sun, A novel method for protein subcellular localization: Combining residue-couple model and SVM, Proceedings of Third Asia-Pacific Bioinformatics Conference, Singapore, 17-21 January 2005, pp. 117-129.