Virtual screening with support vector machines and structure kernels

Combinatorial Chemistry and High Throughput Screening

Volumn 12, Issue 4, 2009, Pages 409-423

  Mahé, Pierre ^a   Vert, Jean Philippe ^b  

^a XEROX RESEARCH CENTRE EUROPE   (France)

^b PSL RESEARCH UNIVERSITY   (France)

Author keywords

Graph kernels; Support vector machines; Virtual screening

Indexed keywords

ALGORITHM; ARTICLE; COMPARATIVE STUDY; HIGH THROUGHPUT SCREENING; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; VIRTUAL SCREENING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASES, FACTUAL; DRUG EVALUATION, PRECLINICAL; LIGANDS; PHARMACEUTICAL PREPARATIONS;

EID: 66249119400     PISSN: 13862073     EISSN: None     Source Type: Journal    
DOI: 10.2174/138620709788167926     Document Type: Article

References (65)

1. Hastie, T.; Tibshirani, R.; Friedman, J. The elements of statistical learning: data mining, inference, and prediction; Springer, 2001.
2. Willett, P. Drug Discov. Today, 2006, 11, 1046-1053.
3. Ivanciuc, O. Anal. Chim. Acta, 1999, 384, 271-284.
4. Goulon, A.; Picot, T.; Duprat, A.; Dreyfus, G. SAR QSAR Environ. Res., 2007, 18, 141-153.
5. Vapnik, V. N. Statistical Learning Theory; Wiley: New-York, 1998.
6. Schölkopf, B.; Smola, A. J. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond; MIT Press, 2002.
7. Shawe-Taylor, J.; Cristianini, N. Kernel Methods for Pattern Analysis; Cambridge University Press, 2004.
8. Schölkopf, B.; Tsuda, K.; Vert, J.-P. Kernel Methods in Computa- tional Biology; MIT Press, 2004.
9. Burbidge, R.; Trotter, M.; Buxton, B.; Holden, S. Comput. Chem, 2001, 26, 4-15.
10. Weston, J.; PÉrez-Cruz, F.; Bousquet, O.; Chapelle, O.; Elisseeff, A.; Schölkopf, B. Bioinformatics, 2003, 19, 764-771.
11. Arimoto, R.; Prasad, M.- A.; Gifford, E.M. J. Biomol. Screen., 2005, 10, 197-205.
12. Briem, H.; Günther, J. ChemBioChem, 2005, 6, 558-566.
13. Liu, H. X.; Zhang, R. S.; Yao, X., J.; Liu, M. C.; Hu, Z. D.; Fan, B. T. J. Comput.-Aided Mol. Des., 2004, 18, 389-399.
14. Saeh, J.; Lyne, P.; Takasaki, B.; Cosgrove, D. J. Chem. Inf. Model., 2005, 45,1122-1133.
15. Tobita, M.; Nishikawa, T.; Nagashima, R. Bioorg. Med. Chem. Lett., 2005, 15, 2886-2890.
16. Kramer, S.; Frank, E.; Helma, C. SAR QSAR Environ. Res., 2002, 13, 509-523.
17. Helma, C.; Cramer, T.; Kramer, S.; De Raedt, L. J. Chem. Inf. Comput. Sci., 2004, 44, 1402-1411.
18. Luan, F.; Zhang, R.; Zhao, C.; Yao, X.; Liu, M.; Hu, Z.; Fan, B. Chem. Res. Toxicol., 2005, 18, 198-203.
19. Byvatov, E.; Fechner, U.; Sadowski, J.; Schneider, G. J. Chem. Inf. Comput. Sci., 2003, 43, 1882-1889.
20. Müller, K.- R.; Rätsch, G.; Sonnenburg, S.; Mika, S.; Grimm, M.; Heinrich, N. J. Chem. Inf. Model., 2005, 45, 249-253.
21. Takaoka, Y.; Endo, Y.; Yamanobe, S.; Kakinuma, H.; Okubo, T.; Shimazaki, Y.; Ota, T.; Sumiya, S.; Yoshikawa, K. J. Chem. Inf. Comput. Sci., 2003, 43, 1269-1275.
22. Doniger, S.; Hofmann, T.; Yeh, J. J. Comput. Biol., 2002, 9, 849-864.
23. Aires-de Sousa, J.; Gasteiger, J. J. Comb. Chem., 2005, 7, 298-301.
24. Lind, P.; Maltseva, T. J. Chem. Inf. Comput. Sci., 2003, 43, 1855-1859.
25. Liu, H. X.; Zhang, R. S.; Yao, X. J.; Liu, M. C.; Hu, Z. D.; Fan, B. T. J. Chem. Inf. Comput. Sci., 2004, 44, 161-167.
26. Ivanciuc, O. Reviews in Computational Chemistry: Wiley-VCH, 2007, Vol. 23, Chap. 6, 291-400.
27. Kashima, H.; Tsuda, K.; Inokuchi, A. In Proceedings of the Twen- tieth International Conference on Machine Learning; AAAI Press, 2003, 321-328.
28. Gärtner, T.; Flach, P.; Wrobel, S. In Proceedings of the Sixteenth Annual Conference on Computational Learning Theory and the Seventh Annual Workshop on Kernel Machines, Lecture Notes in Computer Science: Heidelberg, 2003, 2777, 129-143.
29. Kashima, H.; Tsuda K.; Inokuchi, A. In Kernel Methods in Computational Biology; MIT Press, 2004, Chap. 7, 155-170.
30. MahÉ, P.; Ueda, N.; Akutsu, T.; Perret, J.- L.; Vert, J.-P. J. Chem. Inf. Model., 2005, 45, 939-951.
31. Ralaivola, L.; Swamidass, S. J.; Saigo, H.; Baldi, P. Neural Netw., 2005, 18, 1093-1110.
32. Swamidass, S. J.; Chen, J.; Bruand, J.; Phung, P.; Ralaivola, L.; Baldi, P. Bioinformatics, 2005, 21, S1, i359-i368.
33. MahÉ, P.; Ralaivola, L.; Stoven, V.; Vert, J.-P. J. Chem. Inf. Model., 2006, 46, 2003-2014.
34. Azencott, C.- A.; Ksikes, A.; Swamidass, S. J.; Chen, J. H.; Ra- laivola, L.; Baldi, P. J. Chem. Inf. Model., 2007, 47, 965-974.
35. Boser, B. E.; Guyon, I. M.; Vapnik, V. N. In Proceedings of the 5th annual ACM workshop on Computational Learning Theory; ACM Press, 1992, 144-152.
36. Aronszajn, N. Trans. Am. Math. Soc., 1950, 68, 337-404.
37. Yamanishi, Y.; Bach, F.; Vert, J.-P. Bioinformatics, 2007, 23, 1211-1216.
38. Lodhi, H.; Saunders, C.; Shawe-Taylor, J.; Cristianini, N.; Watkins, C. J. Mach. Learn. Res., 2002, 2, 419-444.
39. Collins, M.; Duffy, N. Adv. Neural. Inform. Proc. Syst., MIT Press, 2001, Vol. 14, 625-632.
40. Leach, A. R.; Gillet, V. J. An introduction to chemoinformatics; Kluwer Academic Publishers, 2003.
41. Gasteiger, J. Handbook of Chemoinformatics.; Wiley-VCH, 2003.
42. Gärtner, T. Exponential and Geometric Kernels for Graphs; NIPS Workshop on Unreal Data: Principles of Modeling Nonvectorial Data, 2002.
43. Morgan, H. L. J. Chem. Doc., 1965, 5, 107-113.
44. Ramon, J.; Gärtner, T. In Proceedings of the First International Workshop on Mining Graphs, Trees and Sequences, 2003, 65-74.
45. MahÉ, P.; Vert, J.-P. Graph kernels based on tree patterns for molecules; Technical Report ccsd-00095488, HAL, 2006.
46. Leslie, C.; Eskin, E.; Noble, W.S. In Proceedings of the Pacific Symposium on Biocomputing 2002; World Scientific, 2002, 564-575.
47. Vishwanathan, S. V. N.; Borgwardt, K.; Schraudolph, N. Adv. Neural. Inform. Proc. Sys t.; MIT Press, 2007. Vol. 19.
48. Brown, R. D.; Martin, Y.C. J. Chem. Inf. Comput. Sci., 1997, 37, 1-9.
49. Matter, H.; Pötter, T. J. Chem. Inf. Comput. Sci., 1999, 39, 1211-1225.
50. McGregor, M. J.; Muskal, S. M. J. Chem. Inf. Comput. Sci., 1999, 39, 569-574.
51. Haussler, D. Convolution Kernels on Discrete Structures; Techni- cal Report UCSC-CRL-99-10: UC Santa Cruz, 1999.
52. Pickett, S. D.; Mason, J. S.; McLay, I. M. J. Chem. Inf. Comput. Sci., 1996, 36, 1214-1223.
53. Dietterich, T. G.; Lathrop, R. H.; Lozano-Perez, T. Artif. Intell., 1997, 89, 31-71.
54. Andrews, S.; Hofmann, T.; Tsochantaridis, I. In Proceedings of the Eighteenth National Conference on Artificial Intelligence; Ameri- can Association for Artificial Intelligence, 2002, 943-944.
55. Gärtner, T.; Flach, P. A.; Kowalczyk, A.; Smola, A. J. In Proceed- ings of the Nineteenth International Conference on Machine Learn- ing; Morgan Kaufmann, 2002, 179-186.
56. Blaschko, M. B.; Hofmann, T. NIPS 2006 Workshop on Learning to Compare Examples; 2006.
57. Lipinski, C.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Adv. Drug Deliv. Rev., 2001, 46, 3-26.
58. King, R. D.; Muggleton, S. H.; Srinivasan, A.; Sternberg, M. J. Proc. Natl. Acad. Sci. USA, 1996, 93, 438-442.
59. Böhm, H.- J.; Schneider, G.; Mannhold, R.; Kubinyi, H.; Folkers, G. Protein-ligand interactions; Wiley, 2003.
60. Brown, R. D.; Martin, Y. C. J. Chem. Inf. Comput. Sci., 1996, 36, 572-584.
61. Gillet, V.; Willett, P.; Bradshaw, J. J. Chem. Inf. Comput. Sci., 2003, 43, 338-345.
62. Lanckriet, G. R. G.; Cristianini, N.; Jordan, M. I.; Noble, W. S. In Kernel Methods in Computational Biology; MIT Press, 2004, Chap. 11, 231-259.
63. HorvÁth, T.; Gärtner, T.; Wrobel, S. In Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining; ACM Press, 2004, 158-167.
64. Borgwardt, K. M.; Kriegel, H.-P. In Proceedings of the fifth Inter- national Conference on Data Mining; IEEE Computer Society, 2005, 74-81.
65. Fröhlich, H.; Wegner, J. K., Sieker, F.; Zell, A. In Proceedings of the 22nd International Conference on Machine Learning; ACM Press, 2005, 225-232.