MoleculeNet: A benchmark for molecular machine learning

Chemical Science

Volumn 9, Issue 2, 2018, Pages 513-530

  Wu, Zhenqin ^a   Ramsundar, Bharath ^b   Feinberg, Evan N ^c   Gomes, Joseph ^a   Geniesse, Caleb ^c   Pappu, Aneesh S ^b   Leswing, Karl ^d   Pande, Vijay ^a  

^a STANFORD UNIVERSITY   (United States)

^b Stanford University   (United States)

^c STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d SCHRÖDINGER INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BENCHMARKING; LEARNING SYSTEMS; MOLECULAR PHYSICS; QUANTUM THEORY;

ACCURATE PREDICTION; DATA SCARCITY; IMBALANCED CLASSIFICATION; MOLECULAR MACHINES; MOLECULAR PROPERTIES; OPEN SOURCE IMPLEMENTATION; OPEN-SOURCE LIBRARIES; QUANTUM MECHANICAL;

LEARNING ALGORITHMS;

EID: 85040102038     PISSN: 20416520     EISSN: 20416539     Source Type: Journal    
DOI: 10.1039/c7sc02664a     Document Type: Article

References (83)

1. J. Gasteiger J. Zupan Angew. Chem., Int. Ed. 1993 32 503 527
2. J. Zupan and J. Gasteiger, Neural networks in chemistry and drug design, John Wiley & Sons, Inc., 1999
3. A. Varnek I. Baskin J. Chem. Inf. Model. 2012 52 1413 1437
4. J. B. Mitchell Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2014 4 468 481
5. J. Devillers, Neural networks in QSAR and drug design, Academic Press, 1996
6. G. Schneider P. Wrede Prog. Biophys. Mol. Biol. 1998 70 175 222
7. Y. LeCun Y. Bengio G. Hinton Nature 2015 521 436 444
8. J. Schmidhuber Neural Network 2015 61 85 117
9. J. Ma R. P. Sheridan A. Liaw G. E. Dahl V. Svetnik J. Chem. Inf. Model. 2015 55 263 274
10. B. Ramsundar, S. Kearnes, P. Riley, D. Webster, D. Konerding and V. Pande, 2015, arXiv preprint arXiv:1502.02072
11. T. Unterthiner, A. Mayr, G. Klambauer, M. Steijaert, J. Wenger, H. Ceulemans and S. Hochreiter, Deep Learning and Representation Learning Workshop (NIPS 2014), 2014
12. I. Wallach, M. Dzamba and A. Heifets, 2015, arXiv preprint arXiv:1510.02855
13. J. S. Delaney J. Chem. Inf. Model. 2004 44 1000 1005
14. A. Lusci G. Pollastri P. Baldi J. Chem. Inf. Model. 2013 53 1563 1575
15. D. L. Mobley K. L. Wymer N. M. Lim J. P. Guthrie J. Comput.-Aided Mol. Des. 2014 28 135 150
16. D. L. Mobley J. P. Guthrie J. Comput.-Aided Mol. Des. 2014 28 711 720
17. M. Rupp A. Tkatchenko K.-R. Müller O. A. V. Lilienfeld Phys. Rev. Lett. 2012 108 058301
18. G. Montavon M. Rupp V. Gobre A. Vazquez-Mayagoitia K. Hansen A. Tkatchenko K.-R. Müller O. A. V. Lilienfeld New J. Phys. 2013 15 095003
19. K. T. Schütt, F. Arbabzadah, S. Chmiela, K. R. Müller and A. Tkatchenko, 2016, arXiv preprint arXiv:1609.08259
20. R. T. McGibbon A. G. Taube A. G. Donchev K. Siva F. Hernández C. Hargus K.-H. Law J. L. Klepeis D. E. Shaw J. Chem. Phys. 2017 147 161725
21. D. Rogers M. Hahn J. Chem. Inf. Model. 2010 50 742 754
22. D. Duvenaud, D. Maclaurin, J. Aguilera-Iparraguirre, R. Gómez-Bombarelli, T. Hirzel, A. Aspuru-Guzik and R. P. Adams, 2015, arXiv preprint arXiv:1509.09292
23. S. Kearnes, K. McCloskey, M. Berndl, V. Pande and P. Riley, 2016, arXiv preprint arXiv:1603.00856
24. G. A. Miller Commun. ACM 1995 38 39 41
25. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li and L. Fei-Fei, CVPR09, 2009
26. O. Russakovsky J. Deng H. Su J. Krause S. Satheesh S. Ma Z. Huang A. Karpathy A. Khosla M. Bernstein A. C. Berg L. Fei-Fei Int. J. Comput. Vis. 2015 115 211 252
27. A. Krizhevsky, I. Sutskever and G. E. Hinton, NIPS Proceedings, 2012
28. C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke and A. Rabinovich, 2014, arXiv preprint arXiv:1409.4842
29. K. He, X. Zhang, S. Ren and J. Sun, 2015, arXiv preprint arXiv:1512.03385
30. DeepChem: Deep-learning models for Drug Discovery and Quantum Chemistry, http://github.com/deepchem/deepchem, accessed 2017-09-27
31. F. Pedregosa G. Varoquaux A. Gramfort V. Michel B. Thirion O. Grisel M. Blondel P. Prettenhofer R. Weiss V. Dubourg et al. J. Mach. Learn. Res. 2011 12 2825 2830
32. M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean and M. Devin, et al., 2016, arXiv preprint arXiv:1603.04467
33. R. P. Sheridan J. Chem. Inf. Model. 2013 53 783 790
34. E. E. Bolton Y. Wang P. A. Thiessen S. H. Bryant Annu. Rep. Comput. Chem. 2008 4 217 241
35. T. Wang J. Xiao T. O. Suzek J. Zhang J. Wang Z. Zhou L. Han K. Karapetyan S. Dracheva B. A. Shoemaker E. Bolton A. Gindulyte S. H. Bryant Nucleic Acids Res. 2012 40 D400 D412
36. S. Gražulis D. Chateigner R. T. Downs A. Yokochi M. Quirós L. Lutterotti E. Manakova J. Butkus P. Moeck A. Le Bail J. Appl. Crystallogr. 2009 42 726 729
37. C. R. Groom I. J. Bruno M. P. Lightfoot S. C. Ward Acta Crystallogr., Sect. B: Struct. Sci., Cryst. Eng. Mater. 2016 72 171 179
38. H. Berman K. Henrick H. Nakamura Nat. Struct. Mol. Biol. 2003 10 980
39. Quantum Machine, http://quantum-machine.org/datasets/, accessed 2017-09-27
40. D. Weininger J. Chem. Inf. Comput. Sci. 1988 28 31 36
41. L. C. Blum J.-L. Reymond J. Am. Chem. Soc. 2009 131 8732 8733
42. R. Ramakrishnan M. Hartmann E. Tapavicza O. A. V. Lilienfeld J. Chem. Phys. 2015 143 084111
43. L. Ruddigkeit R. V. Deursen L. C. Blum J.-L. Reymond J. Chem. Inf. Model. 2012 52 2864 2875
44. R. Ramakrishnan P. O. Dral M. Rupp O. A. V. Lilienfeld Sci. Data 2014 1 140022
45. Experimental in vitro DMPK and physicochemical data on a set of publicly disclosed compounds
46. S. G. Rohrer K. Baumann J. Chem. Inf. Model. 2009 49 169 184
47. AIDS Antiviral Screen Data, http://wiki.nci.nih.gov/display/NCIDTPdata/AIDS+Antiviral+Screen+Data, accessed 2017-09-27
48. R. Wang X. Fang Y. Lu S. Wang J. Med. Chem. 2004 47 2977 2980
49. R. Wang X. Fang Y. Lu C.-Y. Yang S. Wang J. Med. Chem. 2005 48 4111 4119
50. Z. Liu Y. Li L. Han J. Li J. Liu Z. Zhao W. Nie Y. Liu R. Wang Bioinformatics 2014 31 405 412
51. G. Subramanian B. Ramsundar V. Pande R. A. Denny J. Chem. Inf. Model. 2016 56 1936 1949
52. I. F. Martins A. L. Teixeira L. Pinheiro A. O. Falcao J. Chem. Inf. Model. 2012 52 1686 1697
53. Tox21 Challenge, http://tripod.nih.gov/tox21/challenge/, accessed 2017-09-27
54. A. M. Richard R. S. Judson K. A. Houck C. M. Grulke P. Volarath I. Thillainadarajah C. Yang J. Rathman M. T. Martin J. F. Wambaugh T. B. Knudsen J. Kancherla K. Mansouri G. Patlewicz A. J. Williams S. B. Little K. M. Crofton R. S. Thomas Chem. Res. Toxicol. 2016 29 1225 1251
55. M. Kuhn I. Letunic L. J. Jensen P. Bork Nucleic Acids Res. 2016 44 D1075 D41079
56. H. Altae-Tran, B. Ramsundar, A. S. Pappu and V. Pande, 2016, arXiv preprint arXiv:1611.03199
57. Medical Dictionary for Regulatory Activities, http://www.meddra.org/, accessed 2017-09-27
58. K. M. Gayvert N. S. Madhukar O. Elemento Cell Chem. Biol. 2016 23 1294 1301
59. A. V. Artemov E. Putin Q. Vanhaelen A. Aliper I. V. Ozerov A. Zhavoronkov bioRxiv, Biochem. 2016 095653
60. P. A. Novick O. F. Ortiz J. Poelman A. Y. Abdulhay V. S. Pande PLoS One 2013 8 11 e79568
61. Aggregate Analysis of ClincalTrials.gov (AACT) Database, http://www.ctti-clinicaltrials.org/aact-database, accessed 2017-09-27
62. G. W. Bemis M. A. Murcko J. Med. Chem. 1996 39 2887 2893
63. G. Landrum, RDKit: Open-Source Cheminformatics Software, http://www.rdkit.org/
64. A. N. Jain A. Nicholls J. Comput.-Aided Mol. Des. 2008 22 133 139
65. T. Hastie, R. Tibshirani and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, 2009
66. J. Davis and M. Goadrich, Proceedings of the 23rd International Conference on Machine Learning, 2006
67. R. Gómez-Bombarelli, D. Duvenaud, J. M. Hernández-Lobato, J. Aguilera-Iparraguirre, T. D. Hirzel, R. P. Adams and A. Aspuru-Guzik, 2016, arXiv preprint arXiv:1610.02415
68. J. D. Durrant J. A. McCammon J. Chem. Inf. Model. 2011 51 2897 2903
69. C. Da D. Kireev J. Chem. Inf. Model. 2014 54 2555 2561
70. J. Behler M. Parrinello Phys. Rev. Lett. 2007 98 146101
71. J. S. Smith, O. Isayev and A. E. Roitberg, 2016, arXiv preprint arXiv:1610.08935
72. L. Breiman Mach. Learn. 2001 45 5 32
73. J. H. Friedman Ann. Stat. 2001 1189 1232
74. B. Ramsundar B. Liu Z. Wu A. Verras M. Tudor R. P. Sheridan V. Pande J. Chem. Inf. Model. 2017 57 8 2068 2076
75. S. J. Swamidass C.-A. Azencott T.-W. Lin H. Gramajo S.-C. Tsai P. Baldi J. Chem. Inf. Model. 2009 49 756 766
76. J. Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals and G. E. Dahl, 2017, arXiv preprint arXiv:1704.01212
77. J. Friedman T. Hastie R. Tibshirani et al. Ann. Stat. 2000 28 337 407
78. C. Cortes V. Vapnik Mach. Learn. 1995 20 273 297
79. T. Chen and C. Guestrin, 2016, arXiv preprint arXiv:1603.02754
80. S. Kearnes, B. Goldman and V. Pande, 2016, arXiv preprint arXiv:1606.08793
81. I. I. Baskin V. A. Palyulin N. S. Zefirov J. Chem. Inf. Comput. Sci. 1997 37 715 721
82. D. B. Kireev J. Chem. Inf. Comput. Sci. 1995 35 175 180
83. O. Vinyals, S. Bengio and M. Kudlur, 2015, arXiv preprint arXiv:1511.06391