{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T09:10:05Z","timestamp":1774602605937,"version":"3.50.1"},"reference-count":37,"publisher":"American Chemical Society (ACS)","issue":"7","license":[{"start":{"date-parts":[[2020,6,22]],"date-time":"2020-06-22T00:00:00Z","timestamp":1592784000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,6,22]],"date-time":"2020-06-22T00:00:00Z","timestamp":1592784000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2020,6,22]],"date-time":"2020-06-22T00:00:00Z","timestamp":1592784000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/100005713","name":"Office of the Secretary of Defense","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005713","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"publisher","award":["W911NF19-2-0034"],"award-info":[{"award-number":["W911NF19-2-0034"]}],"id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Chem. Inf. Model."],"published-print":{"date-parts":[[2020,7,27]]},"DOI":"10.1021\/acs.jcim.0c00403","type":"journal-article","created":{"date-parts":[[2020,6,22]],"date-time":"2020-06-22T12:52:51Z","timestamp":1592830371000},"page":"3398-3407","source":"Crossref","is-referenced-by-count":68,"title":["Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning"],"prefix":"10.1021","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1344-5642","authenticated-orcid":true,"given":"Michael E.","family":"Fortunato","sequence":"first","affiliation":[{"name":"Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8271-8723","authenticated-orcid":true,"given":"Connor W.","family":"Coley","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States"}]},{"given":"Brian C.","family":"Barnes","sequence":"additional","affiliation":[{"name":"Detonation Science and Modeling Branch, CCDC Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7192-580X","authenticated-orcid":true,"given":"Klavs F.","family":"Jensen","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States"}]}],"member":"316","published-online":{"date-parts":[[2020,6,22]]},"reference":[{"key":"ref1\/cit1","doi-asserted-by":"publisher","DOI":"10.1021\/acscentsci.7b00355"},{"key":"ref2\/cit2","doi-asserted-by":"publisher","DOI":"10.1002\/chem.201605499"},{"key":"ref3\/cit3","doi-asserted-by":"publisher","DOI":"10.1002\/anie.201912083"},{"key":"ref4\/cit4","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.9b00538"},{"key":"ref5\/cit5","doi-asserted-by":"publisher","DOI":"10.1021\/acscentsci.7b00303"},{"key":"ref6\/cit6","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1007\/978-3-030-30493-5_78","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2019: Workshop and Special Sessions","author":"Karpov P.","year":"2019"},{"key":"ref7\/cit7","doi-asserted-by":"publisher","DOI":"10.1039\/C9SC03666K"},{"key":"ref8\/cit8","doi-asserted-by":"crossref","unstructured":"Chen, B.; Barzilay, R.; Jaakkola, T. S. Path-Augmented Graph Transformer Network, arXiv:1905.12712. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1905.12712 (accessed May 29, 2019).","DOI":"10.26434\/chemrxiv.8214422"},{"key":"ref9\/cit9","unstructured":"Dai, H.; Li, C.; Coley, C. W.; Dai, B.; Song, L. Retrosynthesis Prediction with Conditional Graph Logic Network, arXiv:2001.01408. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/2001.01408 (accessed Jan 6, 2020)."},{"key":"ref10\/cit10","doi-asserted-by":"crossref","unstructured":"Liu, X.; Li, P.; Song, S. Decomposing Retrosynthesis into Reactive Center Prediction and Molecule Generation. bioRxiv 2019, 677849.","DOI":"10.1101\/677849"},{"key":"ref11\/cit11","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.9b00286"},{"key":"ref12\/cit12","doi-asserted-by":"publisher","DOI":"10.1039\/C9SC04944D"},{"key":"ref13\/cit13","doi-asserted-by":"publisher","DOI":"10.1126\/science.aax1566"},{"key":"ref14\/cit14","doi-asserted-by":"publisher","DOI":"10.1038\/nature25978"},{"key":"ref15\/cit15","doi-asserted-by":"publisher","DOI":"10.1039\/C9RE00076C"},{"key":"ref16\/cit16","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jmedchem.9b01919"},{"key":"ref17\/cit17","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/IIPHDW.2018.8388338","volume-title":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","author":"Miko\u0142ajczyk A.","year":"2018"},{"key":"ref18\/cit18","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2015.2438544"},{"key":"ref19\/cit19","unstructured":"Xu, Y.; Jia, R.; Mou, L.; Li, G.; Chen, Y.; Lu, Y.; Jin, Z. Improved Relation Classification by Deep Recurrent Neural Networks with Data Augmentation, arXiv:1601.03651. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1601.03651 (accessed Jan 14, 2016)."},{"key":"ref20\/cit20","unstructured":"Bjerrum, E. J. SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules, arXiv:1703.07076. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1703.07076 (accessed Mar 21, 2017)."},{"key":"ref21\/cit21","unstructured":"Tetko, I. V.; Karpov, P.; Van Deursen, R.; Godin, G. Augmented Transformer Achieves 97% and 85% for Top5 Prediction of Direct and Classical Retro-Synthesis, arXiv:2003.02804. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/2003.02804 (accessed Mar 5, 2020)."},{"key":"ref22\/cit22","unstructured":"Lowe, D. M. Extraction of Chemical Structures and Reactions from the Literature. Ph.D. Thesis, University of Cambridge, 2012."},{"key":"ref23\/cit23","doi-asserted-by":"publisher","DOI":"10.1021\/ci5006614"},{"key":"ref24\/cit24","doi-asserted-by":"publisher","DOI":"10.1021\/ci00057a005"},{"key":"ref25\/cit25","doi-asserted-by":"publisher","DOI":"10.26434\/chemrxiv.12046623.v1"},{"key":"ref26\/cit26","doi-asserted-by":"publisher","DOI":"10.1021\/c160017a018"},{"key":"ref27\/cit27","unstructured":"Landrum, G. RDKit: Open-source cheminformatics. https:\/\/www.rdkit.org\/, 2006; version: 2019.03.3 (accessed Feb 3, 2020)."},{"key":"ref28\/cit28","unstructured":"Srivastava, R. K.; Greff, K.; Schmidhuber, J. Training Very Deep Networks, arXiv:1507.06228. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1507.06228 (accessed July 22, 2015)."},{"key":"ref29\/cit29","first-page":"1929","volume":"15","author":"Srivastava N.","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref30\/cit30","unstructured":"Kingma, D. P.; Ba, J. Adam: A method for stochastic optimization, arXiv:1412.6980. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1412.6980 (accessed Dec 22, 2014)."},{"key":"ref31\/cit31","unstructured":"Abadi, M.; Agarwal, A.; Barham, P.; Brevdo, E.; Chen, Z.; Citro, C.; Corrado, G. S.; Davis, A.; Dean, J.; Devin, M. Tensorflow: Large-scale machine learning on heterogeneous distributed systems, arXiv:1603.04467. arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1603.04467 (accessed Mar 14, 2016)."},{"key":"ref32\/cit32","unstructured":"Chollet, F. Keras. https:\/\/keras.io, 2015."},{"key":"ref33\/cit33","doi-asserted-by":"publisher","DOI":"10.1039\/C9SC05704H"},{"key":"ref34\/cit34","unstructured":"World Health Organization. World Health Organization\nmodel list of essential medicines: 21st list 2019. https:\/\/www.who.int\/medicines\/publications\/essentialmedicines\/en\/ (accessed Jan 27, 2020)."},{"key":"ref35\/cit35","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.3727033"},{"key":"ref36\/cit36","doi-asserted-by":"crossref","unstructured":"Storm, C.; Stine, J.; Kramer, J.\n                      Chemistry and Physics of Energetic Materials\n                      ; Bulusu, S. N., Ed. Kluwer Academic Publishers: Dordrecht, The Netherlands, 1990; pp 605\u2013639.","DOI":"10.1007\/978-94-009-2035-4_27"},{"key":"ref37\/cit37","doi-asserted-by":"crossref","unstructured":"Wilson, W. S.; Bliss, D. E.; Christian, S. L.; Knight, D. J. Explosive Properties of Polynitroaromatics, NWC-TP-7073, Naval Weapons Center China Lake,  CA, 1990.","DOI":"10.21236\/ADA229627"}],"container-title":["Journal of Chemical Information and Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.0c00403","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T17:35:22Z","timestamp":1682530522000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.0c00403"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,22]]},"references-count":37,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2020,7,27]]}},"alternative-id":["10.1021\/acs.jcim.0c00403"],"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.0c00403","relation":{"has-preprint":[{"id-type":"doi","id":"10.26434\/chemrxiv.11811564.v1","asserted-by":"object"},{"id-type":"doi","id":"10.26434\/chemrxiv.11811564","asserted-by":"object"}]},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"value":"1549-9596","type":"print"},{"value":"1549-960X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,22]]}}}