Exploring structural modeling of proteins for kernel-based enzyme discrimination

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2010

Volumn , Issue , 2010, Pages 7-11

  Alvarez, Marco A ^a   Yan, Changhui ^b  

^a Utah State University ^*  (United States)

^b North Dakota State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

10-FOLD CROSS-VALIDATION; ART WORK; GRAPH REPRESENTATION; MODELING STRATEGY; PROTEIN FUNCTION PREDICTION; PROTEIN STRUCTURES; SHORTEST PATH; STRAIGHTFORWARD STRATEGY; STRUCTURAL MODELING;

ARTIFICIAL INTELLIGENCE; ENZYMES;

BIOINFORMATICS;

EID: 77955644610     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIBCB.2010.5510588     Document Type: Conference Paper

References (23)

1. P. D. Dobson and A. J. Doig, "Distinguishing enzyme structures from non-enzymes without alignments," Journal of Molecular Biology, vol. 330, no. 4, pp. 771-783, 2003.
2. -, "Predicting enzyme class from protein structure without alignments," Journal of Molecular Biology, vol. 345, no. 1, pp. 187-199, 2005.
3. B. Schölkopf and A. J. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. The MIT Press, 2001.
4. K. M. M. Borgwardt, Cheng, S. Schönauer, S. V. N. V. Vishwanathan, A. J. J. Smola, and H.-P. P. Kriegel, "Protein function prediction via graph kernels." Bioinformatics, vol. 21, no. suppl 1, 2005.
5. H. Hegyi and M. Gerstein, "The relationship between protein structure and function: a comprehensive survey with application to the yeast genome," Journal of Molecular Biology, vol. 288, no. 1, pp. 147-164, 1999.
6. U. Syed and G. Yona, "Enzyme function prediction with interpretable models," in Computational Systems Biology. Humana Press, 2009, vol. 541, ch. 17, pp. 373-420.
7. D. Lee, O. Redfern, and C. Orengo, "Predicting protein function from sequence and structure," Nature Reviews Molecular Cell Biology, vol. 8, no. 12, pp. 995-1005, 2007.
8. J. C. Whisstock and A. M. Lesk, "Prediction of protein function from protein sequence and structure." Quarterly Reviews of Biophysics, vol. 36, no. 3, pp. 307-340, 2003.
9. G. Pandey, V. Kumar, and M. Steinbach, "Computational approaches for protein function prediction: A survey," Department of Computer Science and Engineering, University of Minnesota, Twin Cities, Tech. Rep. 06-028, 2006.
10. R. Kondor and K. M. Borgwardt, "The skew spectrum of graphs," in Proceedings of the International Conference on Machine Learning, 2008, pp. 496-503.
11. K. Riesen, M. Neuhaus, and H. Bunke, "Graph embedding in vector spaces by means of prototype selection," in Graph-Based Representations in Pattern Recognition, 2007, pp. 383-393.
12. B. Luo, "Spectral embedding of graphs," Pattern Recognition, vol. 36, no. 10, pp. 2213-2230, 2003.
13. T. Gärtner, "A survey of kernels for structured data," SIGKDD Explorations Newsletter, vol. 5, no. 1, pp. 49-58, 2003.
14. F. Camastra and A. Petrosino, "Kernel methods for graphs: A comprehensive approach," in Knowledge-Based Intelligent Information and Engineering Systems, 2008, pp. 662-669.
15. H. Bunke and K. Riesen, "A family of novel graph kernels for structural pattern recognition," in Progress in Pattern Recognition, Image Analysis and Applications, 2008, pp. 20-31.
16. T. Gartner, P. Flach, and S. Wrobel, "On graph kernels: Hardness results and efficient alternatives," in Proceedings of the Annual Conference on Computational Learning Theory and 7th Kernel Workshop, 2003, pp. 129-143.
17. J. Ramon and T. Gärtner, "Expressivity versus efficiency of graph kernels," in Proceedings of the International Workshop on Mining Graphs, Trees and Sequences, 2003, pp. 65-74.
18. T. Horváth, T. Gärtner, and S. Wrobel, "Cyclic pattern kernels for predictive graph mining," in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004, pp. 158-167.
19. T. Horváth, "Cyclic pattern kernels revisited," Advances in Knowledge Discovery and Data Mining, pp. 791-801, 2005.
20. K. M. Borgwardt and H. P. Kriegel, "Shortest-path kernels on graphs," in IEEE International Conference on Data Mining, 2005, pp. 8+.
21. S. F. Altschul, T. L. Madden, A. A. Schäffer, J. Zhang, Z. Zhang, W. Miller, and D. J. Lipman, "Gapped BLAST and PSI-BLAST: a new generation of protein database search programs." Nucleic Acids Research, vol. 25, no. 17, pp. 3389-3402, 1997.
22. A. Ben-Hur, C. S. Ong, S. Sonnenburg, B. Schölkopf, and G. Rätsch, "Support vector machines and kernels for computational biology," PLoS Computational Biology, vol. 4, no. 10, pp. e1 000 173+, 2008.
23. H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, and P. E. Bourne, "The protein data bank." Nucleic Acids Research, vol. 28, no. 1, pp. 235-242, 2000.