How far could we go with open data - A case study for TRPV1 antagonists

Molecular Informatics

Volumn 32, Issue 5-6, 2013, Pages 555-562

  Tsareva, Daria A ^a   Ecker, Gerhard F ^a  

^a UNIVERSITY OF VIENNA   (Austria)

Author keywords

Classification; GRIND; Open data; TRPV1

Indexed keywords

ASSAYS; COMPUTATIONAL CHEMISTRY; GRINDING (MACHINING); QUALITY CONTROL;

BIOLOGICAL ASSAYS; CASE-STUDIES; CLASSIFICATION ALGORITHM; DRUG DISCOVERY; GRIND; INDISPENSABLE TOOLS; OPEN DATUM; STRUCTURE-ACTIVITY RELATIONSHIPS; TRANSIENT RECEPTOR POTENTIAL VANILLOID; TRANSIENT RECEPTOR POTENTIAL VANILLOID TYPE 1;

CLASSIFICATION (OF INFORMATION);

VANILLOID RECEPTOR 1; VANILLOID RECEPTOR 1 ANTAGONIST;

ARTICLE; CLASSIFICATION ALGORITHM; DRUG CONFORMATION; HUMAN; HUMAN CELL; IC 50; LEARNING ALGORITHM; MACHINE LEARNING; MOLECULAR INTERACTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SENSITIVITY AND SPECIFICITY; STRUCTURE ACTIVITY RELATION;

EID: 84879764686     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201300019     Document Type: Article

References (41)

1. J. Overington, J. Comput. Aided Mol. Des. 2009, 23, 195.
2. E. E. Bolton, W. Yanli, P. A. Thiessen, S. H. Bryant, in Annual Reports in Computational Chemistry, Vol. 4, American Chemical Society, Washington, DC, 2008.
3. C. Knox, V. Law, T. Jewison, P. Liu, S. Ly, A. Frolkis, A. Pon, K. Banco, C. Mak, V. Neveu, Y. Djoumbou, R. Eisner, A. C. Guo, D. S. Wishart, Nucleic Acids Res. 2011, 39 (Suppl 1), D1035.
4. J. L. Sharman, C. P. Mpamhanga, M. Spedding, P. Germain, B. Staels, C. Dacquet, V. Laudet, A. J. Harmar, Nucleic Acids Res. 2011, 39 (Suppl 1), D534.
5. M. Vogt, J. Bajorath, in Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, Medical Information Science Reference, 2011, p. 190.
6. V. Svetnik, A. Liaw, C. Tong, J. C. Culberson, R. P. Sheridan, B. P. Feuston, J. Chem. Inf. Comput. Sci. 2003, 43, 1947.
7. L. S. Premkumar, AAPS J. 2010, 12, 361.
8. P. R. Kym, M. E. Kort, C. W. Hutchins, Biochem. Pharmacol. 2009, 78, 211.
9. B. Zdrazil, M. Pinto, P. Vasanthanathan, A. J. Williams, L. Z. Balderud, O. Engkvist, C. Chichester, A. Hersey, J. P. Overington, G. F. Ecker, Mol. Inform. 2012, 31, 599.
10. M. C. Jetter, M. A. Youngman, J. J. McNally, S. P. Zhang, A. E. Dubin, N. Nasser, S. L. Dax, Bioorg. Med. Chem. Lett. 2004, 14, 3053.
11. S. A. Wildman, G. M. Crippen, J. Chem. Inf. Comput. Sci. 1999, 39, 868.
12. J. Gasteiger, M. Marsili, Tetrahedron 1980, 36, 3219.
13. G. Cruciani, M. Pastor, W. Guba, Eur. J. Pharmac. Sci. 2000, 29.
14. P. Labute, J. Mol. Graph. Model. 2000, 18, 464.
15. MOE, 2010.
16. V. Batagelj, H.-H. Bock, A. Ferligoj, A. Žiberna, Data Scienca and Classification, Springer, Berlin, 2006.
17. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, I. H. Witten, SIGKDD Explorations 2009, 11(1), 10.
18. R. Kohavi, in Proc. 2nd ICKDDM, Silicon Graphics, Inc., 1996, pp. 202.
19. H. Shi, "Best-first Decision Tree Learning", Master Thesis, University of Waikato (Hamilton), 2006.
20. L. Breiman, Machine Learning 2001, 45, 5.
21. D. W. Aha, D. Kibler, M. K. Albert, Machine Learning 1991, 6, 37.
22. N. Friedman, D. Geiger, M. Goldszmindt, Machine Learning 1997, 29, 131.
23. L. Breiman, Machine Learning 1996, 24, 123.
24. G. I. Webb, Machine Learning 2000, 40, 159.
25. Y. Freund, R. E. Schapire, in Proc. 13th Int. Conf. Machine Learning 1996.
26. K. M. Ting, I. H. Witten, in Proc. 14th Int. Conf. Machine Learning, San Francisco, CA, 1997, 367-375.
27. P. Melville, "Creating Diverse Ensemble Classifiers to Reduce Supervision", Doctoral Thesis, University of Texas (Austin), 2005.
28. R. Caruana, A. Niculescu-Mizil, G. Crew, A. Ksikes, in Proc. ICML, 2004.
29. W. Iba, P. Langley, Proc. 9th Int. Conf. Machine Learning 1992, ML92, 233.
30. J. Platt, Fast Training of Support Vector Machines Using Sequential Minimal Optimization. Advances in Kernel Methods-Support Vector Learning (Eds:, B. Schoelkopf, C. Burges, A. Smola,), MIT Press, Cambridge, MA, 1998.
31. M. Pastor, C. Cruciani, I. McLay, S. Pickket, S. Clementi, J. Med. Chem. 2000, 43, 3233.
32. J. Sadowski, J. Gasteiger, G. Klebe, J. Chem. Inf. Comput. Sci. 1994, 34, 1000.
33. A. Duran, G. C. Martinez, M. Pastor, J. Chem. Inf. Model. 2008, 48, 1813.
34. P. Baldi, S. Brunak, Y. Chauvin, C. A. F. Andersen, H. Nielsen, Bioinform. Rev. 2000, 16, 412.
35. M. Gütlein, C. Helma, A. Karwath, S. Kramer, in 19th EuroQSAR, Vol. Book of Abstracts, Vienna, 2012, p. 51.
36. B. S. Brown, R. Keddy, R. J. Perner, S. DiDomenico, J. R. Koenig, T. K. Jinkerson, S. M. Hannick, H. A. McDonald, B. R. Bianchi, P. Honore, P. S. Puttfarcken, R. B. Moreland, K. C. Marsh, C. R. Faltynek, C.-H. Lee, Bioorg. Med. Chem. Lett. 2010, 20, 3291.
37. C. A. Blum, T. Caldwell, X. Zheng, R. Bakthavatchalam, S. Capitosti, H. Brielmann, S. D. Lombaert, M. T. Kershaw, D. Matson, J. E. Krause, D. Cortright, M. Crandall, W. J. Martin, B. A. Murphy, S. Boyce, A. B. Jones, G. Mason, W. Rycroft, H. Perrett, R. Conley, N. Burnaby-Davies, B. L. Chenard, K. J. Hodgetts, J. Med. Chem. 2010, 53, 3330.
38. A. D. Lebsack, B. J. Branstetter, M. D. Hack, W. Xiao, M. L. Peterson, N. Nasser, M. P. Maher, H. Ao, A. Bhattacharya, M. Kansagara, B. P. Scott, L. Luo, R. Rynberg, M. Rizzolio, S. R. Chaplan, A. D. Wickenden, J. Guy Breitenbucher, Bioorg. Med. Chem. Lett. 2009, 19, 40.
39. Y. Shishido, M. Jinno, T. Ikeda, F. Ito, M. Sudo, N. Makita, A. Ohta, A. Iki-Taki, T. Ohmi, Y. Kanai, T. Tamura, M. Shimojo, Bioorg. Med. Chem. Lett. 2008, 18, 1072.
40. A. J. Williams, L. Harland, P. Groth, S. Pettifer, C. Chichester, E. L. Willighagen, C. T. Evelo, N. Blomberg, G. Ecker, C. Goble, B. Mons, Drug Discov. Today 2012, 17, 1188.
41. B. Zdrazil, N. Blomberg, G. F. Ecker, Mol. Inform. 2012, 31, 528.