Nonlinear SVM approaches to QSPR/QSAR studies and drug design

Current Computer-Aided Drug Design

Volumn 3, Issue 4, 2007, Pages 263-289

  Doucet, Jean Pierre ^a   Barbault, Florent ^a   Xia, Hairong ^a   Panaye, Annick ^a   Fan, Botao ^a  

^a UNIVERSITÉ PARIS DIDEROT   (France)

Author keywords

Classification; Correlation; Drug design; QSPR QSAR; Support vector machine (SVM)

Indexed keywords

CLASSIFICATION (OF INFORMATION); CORRELATION METHODS;

CORRELATION; DRUG DESIGN; NON-LINEAR METHODS; NONLINEAR APPROACH; NONLINEAR SUPPORT VECTOR MACHINES; QSAR STUDIES; QSPR/QSAR; STUDY DESIGN; SUPPORT VECTOR MACHINE; SUPPORT VECTORS MACHINE;

SUPPORT VECTOR MACHINES;

1 [(2 HYDROXYETHOXY)METHYL] 6 (PHENYLTHIO)THYMINE; 1,4 DIHYDROPYRIDINE DERIVATIVE; 1,5 DIARYLIMIDAZOLE DERIVATIVE; ALBUMIN; ANTICOAGULANT AGENT; AROMATIC COMPOUND; BLOOD CLOTTING FACTOR 10A INHIBITOR; CALCIUM CHANNEL BLOCKING AGENT; CYCLOOXYGENASE 2 INHIBITOR; CYTOCHROME P450 3A4; CYTOCHROME P450 INHIBITOR; DIHYDROFOLATE REDUCTASE; EPOTHILONE DERIVATIVE; GLUCAGON DERIVATIVE; GLYCOPROTEIN P; IMIDAZOLE DERIVATIVE; NITROSO DERIVATIVE; NONSTEROID ANTIINFLAMMATORY AGENT; PEPTIDE DERIVATIVE; PESTICIDE; PHENOL DERIVATIVE; PHOSPHOTRANSFERASE INHIBITOR; PYRIMIDINE DERIVATIVE; SULFONAMIDE; THROMBIN INHIBITOR; UNCLASSIFIED DRUG;

ANOREXIA; ANTIVIRAL ACTIVITY; ARTIFICIAL NEURAL NETWORK; BIOCHEMISTRY; BLOOD BRAIN BARRIER; BREAST CANCER; CAPILLARY ELECTROPHORESIS; CARDIOVASCULAR DISEASE; CHEMISTRY; CORRELATION ANALYSIS; DRUG BIOAVAILABILITY; DRUG DESIGN; DRUG SYNTHESIS; ENZYME INHIBITION; HIGH THROUGHPUT SCREENING; HUMAN; IC 50; INTERMETHOD COMPARISON; INTESTINE ABSORPTION; ION EXCHANGE CHROMATOGRAPHY; MATHEMATICAL COMPUTING; MICROARRAY ANALYSIS; MUTAGENICITY; NONHUMAN; NONLINEAR SYSTEM; PHYSICAL CHEMISTRY; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; REGRESSION ANALYSIS; REVIEW; SUPPORT VECTOR MACHINE; THALASSEMIA;

EID: 37249038567     PISSN: 15734099     EISSN: None     Source Type: Journal    
DOI: 10.2174/157340907782799372     Document Type: Review

References (194)

1. Vapnik, V.N. The Nature of Statistical learning Theory, Springer: Berlin, 1995.
2. Cortes, C.; Vapnik, V. Support Vector Networks Machine Learning, 1995, 20, 273-297.
3. Zernov, V.V.; Balakin, K.V.; Ivaschzenko, A.A.; Savchuk, N.P.; Pletnev, I.V. J. Chem. Inf. Comput. Sci., 2003, 43, 2048-2056.
4. Mationi, B.E.; Jurs, P.C. J. Chem. Inf. Compul. Sci., 2002, 42, 232-240.
5. Hansch, L.; Leo, C. Exploring QSAR. Fundamentals and Applications in Chemistry and Biology. American Chemical Society, Washington DC, 1996.
6. Dunn, J.; Wold, S.; Edlund, U.; Helberg, S. Quant. Struct-Act. Relat., 1984, 3, 131-137.
7. Dubois, J.E.; Aaron, J.J.; Alcais, P.; Doucet, J.P.; Rothenberg, F.; Uzan, R. J. Amer. Chem. Soc., 1972, 94, 6823-6828.
8. Goethals, G.; Membrey, F.; Ancian, B.; Doucet, J.P. J. Org. Chem., 1978, 43, 4944-4947.
9. Ancian, B.; Membrey, F.; Doucet, J.P. J. Org. Chem., 1978, 43, 1509-1518.
10. Lucic, B.; Nadrajima, D.; Basic, I.; Trinajstic, N. J. Chem. Inf. Compul. Sci., 2003, 43, 1094-1102.
11. Burden, F.R.; Winkler, D. J. Med. Chem., 1999, 42, 3183-3187.
12. Zupan, J.; Gasteiger, J. Anal. Chim. Acta, 1991, 248, 1-30.
13. Zupan, J.; Gasteiger, J. Neural Networks for Chemists, VCH Publishers, 1993.
14. Devillers, J. Neural Networks in QSAR and Drug Design, Academic Press: London, 1996.
15. Agrafiotis, D.K.; Cedeno, W. J. Med. Chem., 2002, 45, 1098-1107.
16. Gunn, S.R. Support vector machine for classification and regression, Technical Report, Image, Speech and Intelligent System Research Group, University of Southampton, UK, 1997. http://www.isis.ecs.soton.ac.uk/isystems/kernel.
17. Burges, C.J.C. Data Mining Knowledge Discovery, 1998, 2, 1-47.
18. (a) Schölkop, B.; Smola, A.J. Learning with Kernels. Support Vector Machines, Regularization, Optimisation and Beyond, The MIT Press, Cambridge, MA, London England, 2002.
19. (b) Smota, A.J.; Schölkopf, B. A tutorial on support vector regression. NeuroCOL2 Technical report series, NC2-TR- 1998-030, October 1998.
20. (a) Belousov, A.I.; Verzakov, S.A., von Frese, J. Chemometr. Intell. Lab. Syst., 2002, 64, 15-25.
21. (b) Belousov A.I.; Versakov S.A.; Von Frese J. J. Chemom., 2002, 16, 482-489.
22. Christianini, N.; Shawe-Taylor, J. An introduction to Support Vector Machines and Other Kernel-Based Functions Learning Methods, Cambridge University Press, 2000.
23. Herbrich, R. Learning Kernel Classifiers: theory and algorithms, MIT Press, 2002.
24. Chang, C.C.; Lin, C.J. A Library for Support Vector Machines. LIBSVM. version 2-31. http://csie.ntu.edu.tw/-cjlin/libsvm/ #nuandone.
25. Thissen, U.; van Brakel, R.; de Weijer, A.P.; Meissen, W.J.; Buydens, L.M.C. Chem. Intell. Lab. Sys., 2003, 69, 35-49. URL http://www.kernel-machines.org.
26. Fröhlich, H.; Wegner, J.K.; Zell, A. QSAR Comb. Sci., 2004, 23, 311-317.
27. Barrett, S.I.; Langdon, W.B. Advances in Application of Machine Learning Techniques in Drug Discovery, Design and Development.
28. Noble, W.S. Support vector machines applications in computational biology In Kernel methods in Computational biology, Schoelkopf, B., Torda, K., Vert, J.P.; Ed. MIT press, 2004, 71-92.
29. Vert, J.P. Classification of biological sequences with kernel methods. Lectures notes in Artificial Intelligence, 2006, 4201,7-18
30. and Kernel method in genomics and computational biology, Technical report HAL:ccsd-00012124, 1-22, 2006.
31. Burbidge, R.; Trotter, M.; Buxton, B.; Holden, S. Computers and Chemistry, 2001, 26, 5-14.
32. Czerminski, R.; Yasri, A.; Hartsough, D. Quant. Struct-Act. Relat., 2001, 20, 227-240.
33. Amendolia, S.R.; Cossu, G.; Ganadu, M.L.; Golosio, B.; Masala, G.L.; Mura, G.M. Chemom. Intel. Lab. Syst., 2003, 69, 13-20.
34. Distante, C.; Ancona, N.; Siciliano, P. Sensors and actuators B, 2003, 88, 30-39.
35. Sanchez, V.D. Neurocomputing, 2003, 55, 5-20.
36. Üstün, B.; Melssen, W.J.; Buydens, L.M.C. Chemometrics and Intelligent Lab. Syst. 2006, 81, 29-40.
37. Lind P.; Maltseva, T. J. Chem. Inf. Comp. Sci., 2003, 43, 1855-1859.
38. Mahé, P.; Ueda, N.; Akutsu, T.; Perret, J.L.; Vert, J.P. J. Chem. Inf. Model., 2005, 45, 939-951.
39. Rücker, G.; Rücker, C. J. Chem. Inf. Comput. Sci., 1993, 33, 683-695.
40. Fröhlich, H.; Wegner, J.K.; Sieker, F.; Zell, A. QSAR Comb. Sci., 2006, 25, 317-326.
41. a) Leslie, C.; Eskin, E.; Weston, J.; Noble, W.S. Bioinformatics, 2004, 20, 467-476.
42. b) Leslie, C.; Eskin, E.; Weston, J.; Noble, W.S. Neural Information Processing System, 2003, 15, 1441-1448.
43. Thissen, U.; Pepers, M.; Ustan, B.; Meissen, W.J.; Buydens, L.M.C. Chemom. Intell. Lab. Syst., 2004, 73, 169-179.
44. Wang, W.J.; Xu, Z.B.; Lu, W.Z.; Zhang, X.Y. Neurocomputing, 2003, 643-663.
45. Scholkopf, B.; Smola, A.J.; Williamson, R.C.; Bartlett, P.L. Neural Comput., 2000, 12, 1207-1245.
46. Liu, H.X.; Zhang, R.S.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf. Comput. Sci., 2003, 43, 1288-1296.
47. Yao, X.J.; Panaye, A.; Doucet, J.P.; Zhang, R.S.; Chen, H.F.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf. Comput. Sci., 2004, 44, 1257-1266.
48. Song, M.; Breneman, C.M.; Bi, J.; Sukumar, N.; Bennett, K.P.; Cramer, S.; Tugcu, N. J. Chem. Inf. Comput. Sci., 2002, 42, 1347- 1357.
49. (a) Suykens, J.A.K.; Vandewalle, J. Inter. J. Circ. Theor. Appl., 1999, 27, 605-615.
50. (b) Suykens, J.A.K., Vandewalle, J., De Moor, B. Neural Networks, 2001, 14, 23-35.
51. Yao, X.J.; Liu, H.K.; Zhang, R.S.; Liu, M.C.; Hu, Z.D.; Panaye, A.; Doucet, J.P.; Fan, B.T. Mol. Pharm., 2005, 2, 348-356.
52. Yean, C.H. Ramaswamy, S.; Tamayo, P.; Mukherjee, S.; Rifkin, R.M.; Angelo, M.; Reich, M.; Lander, E.; Mesirov, J.; Golub, T. Bioinformatics, 2001, 17, Sup., S316-S322.
53. Ding, C.H.Q.; Dubchak, I. Bioinformatics, 2001, 17, 349-358.
54. Platt, J.C.; Cristianini, N., Shawe-Taylor, J. Advances in Neural Information Processing Systems, MIT Press, 2000, 12, 547-553.
55. Weston, J.; Watkins, C. Multi-class Support Vector Machines Technical report CSD-TR-98-04. Royal Holloway, University of London, 1998.
56. Hsu, C.W.; Lin, C.J. IEEE Transactions on Neutral Networks, 2002, 13, 415-425.
57. (a) Katritzky, A.R.; Lobanov, V.S.; Karelson, M. CODESSA Reference Manual, Version 2.0, Gainesville, 1996.
58. (b) Katritzky, A.R.; Lobanov, V.S.; Karelson, M. CODESSA, Training manual, University of Florida, Gainesville, FL, 1995.
59. Todeschini, R.; Consonni, V. Dragon, release 1;12 for Windows, Milano, Italy 2001, http://www.disat.unimib.it/chm.
60. (a) Liu, Y. J. Chem. Inf. Comput. Sci., 2004, 44, 1823-1828.
61. (b) Yu, L.; Liu, H, ICML-03, 2003, 856-863.
62. Selwood, D.L.; Livingstone, D.J.; Comley, J.C.W.; O'Dowd, A.B.; Hudson, A.T.; Jackson, P.; Jandu, K.S.; Rose, V.S.; Stables, J.N. J. Med. Chem., 1990, 33, 136-142.
63. Zheng, W.; Tropsha, A. J. Chem. Inf. Comput. Sci., 2000, 40, 185-194.
64. Sutter, J.M., Dixon, S.L., Jurs, P.C. J. Chem. Inf. Comput. Sci., 1995, 35, 77-84.
65. Luke, B.T. J. Chem. Inf. Comput. Sci., 1994, 34, 1279-1287.
66. Waller, C.L.; Bradley, M.P. J. Chem. Inf. Comput. Sci., 1999, 39, 345-355.
67. Kubinyi, H. Quant. Struct-Act. Relat., 1994, 13, 285-294.
68. Rogers, DR.; Hopfinger, A.J. J. Chem. Inf. Comput. Sci., 1994, 34, 854-866.
69. Yasri, A.; Hartsough, D. J. Chem. Inf. Comput. Sci., 2001, 41, 1218-1277.
70. Hasegawa, K.; MiyashiLa, Y.; Funatsu, K. J. Chem. Inf. Comput. Sci., 1997, 37, 306-310.
71. Hasegawa, K.; Funatsu, K. J. Mol. Struct. (THEOCHEM), 1998, 425, 255-262.
72. Jouan-Rimbaud, D.; Massart, D.L.; de Noord, O.E. Chemom. Intell. Lab. Syst., 1996, 35, 213-220.
73. Nath, R.; Rajagopalan, B.; Ryker, R. Comput. Ops. Res., 1997, 24, 767-773.
74. Kovalishyn, V.; Tetko, V.I.; Luik, A.I.; Kholodovych, V.V.; Villa, A.E.P.; Livingstone, D.J. J. Chem. Inf. Comput. Sci., 1998, 38, 651-659.
75. Todeschini, R.; Galvagni, D.; Vilchez, J.L.; del Olmo, M.; Navas, N. Trends Anal. Chem., 1999, 18, 93-98.
76. Burden, F.R.; Ford, M.G.; Whitley, D.C.; Winkler, D.A. J. Chem. Inf. Comput. Sci., 2000, 40, 1423-1430.
77. Izrailev, S.; Agrafiotis, D.K. J. Chem. Inf. Comput. Sci., 2001, 41, 176-180.
78. Izrailev, S.; Agrafiotis, D.K. SAR QSAR Environ. Res., 2002, 13, 417-423.
79. Tetko, I.V.; Villa, A.E.P.; Livingstone, D.J. J. Chem. Inf. Comput. Sci., 1996, 36, 794-803.
80. Su, Y.; Murali, T.; Pavlovic, V.; Schaffer, M.; Kasif, S. Bioinformatics, 2003, 19, 1578-1579.
81. Krishnapuram, B.; Carin, L.; Hartemink, A. J. Comput. Biol., 2004, 11, 227-242.
82. Guyon, I.; Weston, J.; Barnhill, S.; Vapnik, V. Machine Learning, 2002, 46, 389-422.
83. Weston, J.; Elisseeff, A.; Schölkopf, B.; Tipping, M. JMLR Special Issue on Variable and Feature Selection, 2002, 3, 1439-1461.
84. Rakotomamonjy, B. Journal of Machine Learning Reseach Special Issue on Variable and Feature Selection, 2003, 3, 1357-1370.
85. Byvatov, E.; Schneider, G. J. Chem. Inf. Comput. Sci., 2004, 44, 993-999.
86. Huuskonen, J. J. Chem. Inf. Comput. Sci., 2000, 40, 773-777.
87. Li, H.; Yap, C.W.; Ung, C.Y.; Xue, Y.; Can, Z.W.; Chen, Y.Z. J. Chem. Inf. Model., 2005, 45, 1376-1384.
88. Xue, Y.; Li, Z.R.; Yap, C.W.; Sun, L.Z.; Chen, X.; Chen, Y.Z. J. Chem. Inf. Comput. Sci., 2004, 44, 1630-1638.
89. Yap, C.W.; Chen, Y.Z. J. Chem. Inf. Model, 2005, 45, 982-992.
90. Jorissen, R.N.; Gilson, M.K. J. Chem. Inf. Model., 2005, 45, 549-561.
91. Norinder, U. Neurocomputing, 2003, 55, 337-346.
92. Byvatov, E.; Fechner, U.; Sadowski, J.; Schneider, G. J. Chem. Inf. Comput. Sci., 2003, 43, 1882-1889.
93. Ghose, A.K.; Pritchett, A.; Crippen, G.M. J. Comput. Chem., 1988, 9, 80-90.
94. Schneider, G.; Neidhart, W.; Gillet, T.; Schmid, G. Angew. Chem. Int. Ed. Engl., 1999, 38, 2894-2896.
95. Sadowski, J.; Kubinyi, H. J. Med. Chem., 1998, 41, 3325-3329.
96. Ajay; Walters, W.P.; Murcko, M.A. J. Med. Chem., 1998, 41, 3314-3329.
97. Müller, K-R.; Rätsch, G.; Sonnenburg, S.; Mika, S.; Grimm, M.; Heinrich, N. J. Chem. Inf. Model., 2005, 45, 249-253.
98. Zomer, S.; Sánchez, M.D.N.; Brereton, R.G.; Pavón, J.L.P. Chemometrics, 2004, 18, 294-305.
99. Warmuth, M.K.; Liao, J.; Ratsch, G.; Mathieson, M.; Putts, S.; Lemmen, C. J. Chem. Inf. Comput. Sci., 2003, 43, 667-673.
100. Liu, Y. J. Chem. Inf. Comput. Sci., 2004, 44, 1936-1941.
101. Wilson, D.; Willett, P.; Lawson, K.; Mullier, G. J. Chem. Inf. Comput. Sci., 2003, 43, 469-474.
102. Sach, J.C.; Lyne, P.D.; Takasaki, B.K.; Cosgrove, D.A. J. Chem. Inf. Model., 2005, 45, 1122-1133.
103. Yan, X.J.; Panaye, A.; Doucet, J.P.; Chen, H.F.; Zhang, R.S.; Fan, B.T.; Liu, M.C.; Hu, Z.D. Anal. Chim. Acta, 2005, 535, 259-273.
104. Aptula, A.O.; Nevetza, T.I.; Valkova, I.V.; Cronin, M.T.D.; Schultz, T.W.; Kühne, R.; Schüürmann, G. Quant. Struct-Act. Relat., 2002, 21, 12-22.
105. Ren, S.; Kim, H. J. Chem. Inf. Comput. Sci., 2003, 43, 2106-2110.
106. Ren, S. Toxicol. Lett., 2002, 133, 127-129.
107. Mazzatorta, P.; Cronin, M.T.D.; Benfenati, E. QSAR Comb. Sci., 2006, 25, 616-625.
108. Doniger, S.; Hofmann, T.; Yeh, J. J. Comput. Biol., 2002, 9, 849-864.
109. Andres, C.; Hurter, M.C. QSAR Comb. Sci., 2006, 25, 305-309.
110. Sorich, M.J.; Miners, J.O.; McKinnon, R.A.; Winkler, D.A,; Burden, F.R.; Smith, P.A. J. Chem. Inf. Comput. Sci., 2003, 43, 2019-2024.
111. Kriegl, J.M.; Arnhold, T.; Fox, T. QSAR Comb. Sci., 2005, 24, 491-502.
112. Merkwirth, C.; Mauser, H.; Schulz-Gash, T.; Roche, O.; Stahl, M.; Lengauer, T. J. Chem. Inf. Comput. Sci., 2004, 44, 1971-1978.
113. Xue, Y.; Yap, C.W.; Sun, L.Z.; Cao, Z.W.; Wang, J.F.; Chen, Y.Z. J. Chem. Inf. Comput. Sci., 2004, 44, 1497-1505.
114. Blake, C.L.; Metz, C.J. UCI Repository of Machine Learning Databases, 1998, URL: http://www.ics.uci.edu/-mlearn/ MLPRepository.html.
115. King, R.D.; Muggleton, S.; Lweis, R.A.; Sternberg, M.J.E. Proc. Natl. Acad. Sci. USA, 1992, 89, 11322-11326.
116. Gao, H.; Bajorath, J. Mol. Diversity, 1999, 4, 115-130.
117. Luan, F.; Zhang, R.S.; Zhao, C.Y.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. Chem. Res. Toxicol., 2005, 18, 198-203.
118. Bleckmann, B.; Mciler, J. QSAR Comb. Sci., 2003, 22, 722-728. And Database: www.jens-meiler.de.
119. Liu, H.X.; Zhang, R.S.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Comp. Aid. Mol. Des., 2004, 18, 389-399.
120. Lu, W.; Dong, N.; Naray-Szabo, G. QSAR Comb. Sci., 2005, 24, 1021-1025.
121. Zhao, C.Y.; Zhang, R.S.; Liu, H.X.; Xue, C.X.; Zhan, S.G.; Zhou, X.F.; Liu, M.C.; Fan, B.T. J. Chem. Inf. Comput. Sci., 2004, 44, 2040-2046.
122. Liu, H.X.; Zhang, R.S.; Luan, F.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf. Comp. Sci., 2003, 43, 900-907.
123. Chang, R.F.; Wu, W.J.; Moon, W.K.; Chou, Y.H.; Chen, D.R. Acad. Radiol., 2003, 43, 900-907.
124. Sadik, O.; Land, W.H. Jr; Wanekaya, A.K.; Uematsu, M.; Embrechts, M.J.; Wong, L.; Leibensperger, D.; Volykin, A. J. Chem. Inf. Comput. Sci., 2004, 44, 499-507.
125. Cao, L.J. Neurocomputing, 2003, 51, 321-339.
126. Cai, Y.D.; Liu, X.J.; Xu, X.B.; Chou, K.C. Comput. Chem., 2002, 26, 293-296.
127. Li, L.; Noble, W.S. Proceedings of the Sixth international conference on Computational molecular Biology, 2002, pp 225-232.
128. Busdutti, S.; Abela, J.; Pace, G.J. Genomic informatics, 2004, 15, 191-200.
129. French, L. A survey of remote homology detection and protein superfamily classification, School of computer science. Windsor University, Windsor, Canada, 2005. http://socr.uwindsor.ca
130. Baldi, P.; Chauvin, Y.; Hunkapiller, T.; Mc Clure, M.A. Proc. Natl. Acad. Sci. USA, 1994, 91, 1059-1063.
131. Karplus,K.; Barrett, C.; Hughey, R. Bioinformatics, 1998, 14, 846-856.
132. Jaakkola, T.; Diekhans, M.; Haussler, D. J. Comput. Biol., 2000, 7, 95-114.
133. Krogh, A. Computational methods in molecular biology, Salzberg S.L.; Searls D.B.; Kasif S. Elsevier, 1998, 45-63.
134. Karchin, R.; Karplus, K.; Haussler, D. Bioinformatics, 2002, 18, 147-159.
135. Hou, Y.; Hsu, W.; Lee, M.L.; Bystroff, C. Bioinformatics, 2003, 19, 2294-2301.
136. Cai, Y.D.; Liu, X.J.; Xu, X.B.; Chou, K.C. J. Comput. Chem., 2002, 23, 267-274.
137. Mukherjee, S.; Tamayo, P.; Mesirov, J.; Slonim, D.; Verri, A.; Poggio, T. Support vector machine classification of microarray data. Technical report CBCL. Paper 182/AI Memo 1677 MIT, 1999.
138. Furey, T.S.; Cristianini, N.; Duffy, N.; Bednarski, D.W.; Schummer, M.; Haussler, D. Bioinformatics, 2000, 16, 906-914.
139. Ramaswamy, S.; Tamayo, P.; Rifkin, R.; Mukherjee, S.; Yeang, C.H.; Angelo, M.; Ladd, C.; Reich, M.; Latulippe, E.; Mesirov, J.P.; Poggio, T.; Gerald, W.; Loda, M.; Lander, E.S.; Golub, T.R. Proc. Natl. Acad. Sci. USA, 2001, 98, 15159-15154.
140. Li, Y.; Zhang, C.; Ogibara, M. Bioinformatics, 2004, 20, 2429-2437.
141. a) Lee, Y.; Lee, C-K. Classification of Multiple Cancer types by a Multicategory Support Vector Machines Using Gene Expression Data, Technical report 1051r, University of Wisconsin, WI, USA, 2002.
142. b) Lee, Y.; Lee, C.K. Bioinformatics, 2003, 19, 1132-1139.
143. Ben-Dor, A.; Bruhn, L.; Friedman, N.; Nachman, I.; Schummer, M.; Yakhini, Z. J. Comp. Biol., 2000, 7, 559-584.
144. Brown, M.; Grundy, W.; Lin, D.; Cristianini, N.; Sugnet, C.; Furey, T.; Haussler, D. Knowledge based analysis of micro array gene expression data using support vector machines Technical report UCSC-CRL-99-09, U.C. Santa Cruz, and Proc.. Natl. Acad. Sci. USA, 2000, 97, 262-267.
145. Anderson, D.C.; Li, W.; Payan, D.G.; Noble, W.S. J. Proteome Research, 2003, 2, 137-146.
146. Myasnikova, E.; Samsonova, A.; Samsonova, M.; Reinitz, J. Bioinformatics, 2002, 18, S87-S95.
147. Ren, S. J. Chem. Inf. Comput. Sci., 2003, 43, 1679-1687.
148. Panaye, A.; Fan, B,T.; Doucet, J.P.; Yao, X.J.; Zhang, R.S.; Liu, M.C.; Hu, Z.D. SAR QSAR Environ. Res., 2006, 17, 75-91.
149. Hastic, T.J.; Tibshiram, R.J. Generalized additive models, Chapman and Hall, New York, 1990.
150. Osborne, MR.; Presnell, B.; Turlach, B.A. J. Comput. Graphical Slat., 2000, 9, 319-337.
151. (a) Cleveland, W.S. J. Amer. Stat. Asso., 1979, 74, 829-836.
152. (b) Cleveland, W.S.; Delvin, S.A. J. Amer. Stat. Asso., 1988, 83, 596-610.
153. Friedman, J.H. Annals Stat., 1991, 19, 1-141.
154. Friedman, J.H., Stuetzle, W. J. Amer. Stat. Asso., 1981, 76, 817-823.
155. Cronin, M.T.D.; Manga, N.; Seward, JR.; Sinks, G.D.; Schultz, T.W. Chem. Res. Toxicol., 2001, 14, 1498-1505.
156. Schultz, T.W.; Netvzeva, T.I.; Cronin, M.T.D. SAR QSAR Environ. Res., 2003, 14, 59-81.
157. Mekenyan, O.G.; Veith, G.D. SAR QSAR Environ. Res., 1993, 1, 335-344.
158. Garg, R.; Kurup, A.; Mekapatui, S.B.; Hansch, C. Chem. Rev., 2003, 103, 703-732.
159. Xue, C.X; Zhang, R.S.; Liu, H.X.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf. Comput. Sci., 2004, 44, 1693-1700.
160. Luan F.; Ma W.P.; Zhang X.Y.; Zhang H.X; Liu M.C.; Hu Z.D.; Fan B.T. QSAR Comb. Sci., 2006, 25, 46-55.
161. Zhao, C.Y.; Zhang, HX; Zhang, X.Y.; Liu, M.C.; Hu, Z.D.; Fan, B.T. Toxicology, 2006, 217, 105-119.
162. Chen, H.F.; Yao, X.J.; Petitjean, M.; Xia, H.R., Yao, J.H.; Panaye, A.; Doucet, J.P.; Fan, B.T. QSAR Comb. Sci., 2004, 23, 603-620.
163. Sun, J.; Chen, H.F.; Xia, H.R.; Yao, J.H.; Fan, B.T. QSAR Comb. Sci., 2006, 25, 25-49.
164. Liu, H.X; Hu, R.J.; Zhang, R.S.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Comp. Aid. Mol. Design, 2005, 19, 33-46.
165. Yakowsky, S.H.; Dannelfelser, R.M. The Arizona Database of Aqueous Solubility. College ofPharrnacy, University of Arizona, Tucson, AZ 1990.
166. Syracuse research Corporation. Physical Chemistry property Database (PHYSPROP); SRC Environmental Science Center, Syracuse, NY, USA, 1994.
167. Tetko, LV.; Tanchuk, V.Y.; Kasheva, T.M.; Villa, A.E.P. J. Chem. Inf Comput. Sci., 2001, 41, 1488-1493.
168. Katritzky, A.R.; Wang, Y.; Sild, S.; Tamm, T.; Karelson, M. J. Chem. Inf. Comput. Sci., 1998, 38, 720-725.
169. Catana, C.; Gao, FL; Orrenius, C.; Stouten, P.F.W. J. Chem. Inf. Model., 2005, 45, 170-176.
170. Tugcu, N.; Song, M.; Breneman, C.M.; Sukumar, N.; Bennett, K.P.; Cramer, S.M. Anal. Chem., 2003, 75, 3563-3572.
171. Tugcu, N.; Ladiwala, A.; Breneman, C.M.; Cramer, S.M. Anal. Chem., 2003, 75, 5806-5816.
172. Xue, C.X; Zhang, R.S.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf, Comput. Sci., 2004, 44, 950-957.
173. Liu, H.X.; Zhang, R.S.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. Anal. Chim. Acta., 2004, 1, 31-41.
174. Liu, H.X; Yao, X.J.; Xue, CX; Zhang, R.S.; Liu, M.C.; Hu, Z.D.; Fan, B.T. Anal. Chim. Acta, 2005, 542, 249-259.
175. 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.
176. Luan, F.; Zhang, R.S.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. QSAR Comb. Sci., 2005, 24, 227-239.
177. Liu, H.X; Xue, C.X; Zhang, R.S.; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf. Comput. Sci., 2004, 44, 1979-1986.
178. Xue, C.X; Zhang, R.S.; Liu, H.X; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf. Comput. Sci., 2004, 44, 1267-1274.
179. Xue, C.X; Zhang, R.S.; Liu, H.X; Yao, X.J.; Liu, M.C.; Hu, Z.D.; Fan, B.T. J. Chem. Inf Comput. Sci., 2004, 44, 1979-1986.
180. Tetko, I.V.; Solov'ev, V.P.; Antonov, A.V.; Yao, X.J.; Doucet, J.P.; Fan, B.T.; Hoonakker, F.; Fourches, D.; Jost, P.; Lachiche, N.; Varnek, A. J. Chem. Inf. Model., 2006, 46, 808-819.
181. Helms, C.; Cramer, T.; Cramer, S.; De Raedt, L. J. Chem. Inf. Comput. Sci., 2004, 44, 1402-1411.
182. Huberty, C.J. Applied discriminant analysis, John Wiley & sons, New York, 1994.
183. (a) Wold, S.; Kettaneh-Wold, N.; Skagerberg, B. Chemom. Intell. Lab. Sys, 1989, 7, 53-65.
184. see also Wold, S. Chemom. Intell. Lab. Sys., 1992, 14, 71-84.
185. (b) Wold, S.; Rube, A.; Wold, H.; Dunn, W.J. J. Scientific Stat. Comput., 1984, 5, 735-743.
186. Quinlan, J.R. C4.5: programs for machine learning, Morgan Kaufmann, San Mateo, CA, 1993.
187. Johnson, R.A.; Wichem, D.W. Applied multivariate statistical analysis, Prentice Hall, Englewood Cliffs, NJ, 1982.
188. Hosmer, D.W.; Lemeshow, S. Applied Logistic Regression, Wiley, New York, 1989.
189. Tetko, I.V. J. Chem. Inf. Comput. Sci., 2002, 42, 717-728.
190. Specht, D.F. Probabilistic neural networks. Neural Networks, 1990, 3, 109-118.
191. Niwa, T. J. Chem. Inf. Comput. Sci., 2003, 43, 113-119.
192. Burden, F.R.; Winkler, D.A. Chem. Res. Toxicol., 2000, 13, 436-440.
193. King, R.D.; Muggleton, S.H.; Srinivasan, A.; Stemberg, M.J.E. Proc. Natl. Acad. Sci. USA, 1996, 93, 438-442.
194. Antonov A.V.; Tetko, I.V.; Mader, M.T.; Budezies, J.; Mewes, H.W. Bionformatics, 2004, 20, 644-652.