An MLP-based feature subset selection for HIV-1 protease cleavage site analysis

References 

1. You L, Garwicz D, Rognvaldsson T. Comprehensive bioinformatic analysis of the specificity of human immunodeficiency virus type 1 protease. Journal of Virology. 2005;19:12477–12486
2. Cai Y, Chou K. Artificial neural network model for predicting HIV protease cleavage sites in protein. Advances in Engineering Software. 1998;29:119–128
3. Cai Y, Liu X, Xu X, Chou K. Support vector machines for predicting hiv protease cleavage sites in protein. Journal of Computational Chemistry. 2002;23:267–274
   • MEDLINE
   • CrossRef
4. Thompson T, Chou K, Zheng C. Neural network prediction of the hiv-1 protease cleavage sites. Theoretical biology. 1995;177:369–379
5. Thomson R, Hodgman TC, Yang ZR, Doyle AK. Characterizing proteolytic cleavage site activity using bio-basis function neural networks. Bioinformatics. 2003;19:1741–1747
   • MEDLINE
   • CrossRef
6. Xing E, Jordan M, Karp R. Feature selection for high-dimensional genomic microarray data. In:  Brodley CE,  Danyluk AP editor. Proceedings of the 18th international conference on machine learning. San Francisco, USA: Morgan Kaufmann; 2001;p. 601–608
7. Dougherty ER. Feature-selection overfitting with small-sample classifier design. IEEE Intelligent Systems Magazine. 2005;20(6):64–66
8. Forman G. Feature selection: we’ve barely scratched the surface. IEEE Intelligent Systems. 2005;20(6):74–76
9. Kim H, Zhang Y, Heo YS, Oh HB, Chen SS. Specificity rule discovery in hiv-1 protease cleavage site analysis. Computational Biology and Chemistry. 2008;32:71–78
10. Liu H, Motoda H. Feature selection for knowledge discovery and data mining. Germany: Springer; 1998;
11. Blum AL, Langley P. Selection of relevant features and examples in machine learning. Artificial Intelligence. 1997;97:245–271
12. Liu H, Setiono R. A probabilistic approach to feature selection—a filter solution. In:  Saitta L editors. Proceedings of the 13th international conference on machine learning. San Francisco, USA: Morgan Kaufmann; 1996;p. 319–327
13. Marko RS, Igor K. An adaptation of relief for attribute estimation in regression. In:  Fisher DH editors. Proceedings of the 14th international conference on machine learning. San Francisco, USA: Morgan Kaufmann; 1997;p. 296–304
14. Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. Machine Learning. 2002;46:389–422
15. Manuel M, Enrique S, Gustavo A. Feature selection with a perceptron neural net. In: International workshop on feature selection for data mining (FSDM06). USA: SIAM; 2006;
16. http://www.cs.waikato.ac.nz/ml/weka/ (accessed: 29 June 2009).
17. Jolliffe IT. Principal component analysis. Germany: Springer; 1986;
18. Nguyen DV, Rocke DM. Tumor classification by partial least squares using microarray gene expression data. Bioinformatics. 2002;18:39–50
    • MEDLINE
    • CrossRef
19. Mitchell TM. Machine learning. US: McGraw-Hill International Editions; 1997;
20. Krogh A, Hertz JA. A simple weight decay can improve generalization. In:  Moody JE,  Hanson SJ,  Lippman RP editor. Advances in neural information processing systems 4. Cambridge: Kaufmann; 1992;p. 950–957
21. Kim H. Computationally efficient heuristics for if-then rule extraction from feed-forward neural networks. Lecture Notes in Artificial Intelligence. 2000;170–182
22. http://www.cse.unsw.edu.au/∼mike/roc.pdf (accessed: 29 June 2009).
23. Thrun SB, Bala J, Bloedorn E, Bratko I, Cestnik B, Cheng J, et al. The monk's problems: a performance comparison of different learning algorithms, Technical Report CMU-CS-91-197, Carnegie Mellon University; 1991.
24. Wyse N, Dubes R, Jain AK. A critical evaluation of intrinsic dimensionality algorithms. In:  Geleman ES,  Kanal LN editor. Pattern recognition in practice. San Francisco: Morgan Kaufmann; 1980;p. 415–425
25. Platt J. Sequential minimal optimization: a fast algorithm for training support vector machines. Microsoft Research Technical Report MSR-TR-98-14; 1998.
26. http://weblogo.berkeley.edu/ (accessed: 29 June 2009).