{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:28:57Z","timestamp":1760956137063,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,14]]},"DOI":"10.1145\/3447548.3467120","type":"proceedings-article","created":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T06:12:08Z","timestamp":1628748728000},"page":"2554-2564","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization"],"prefix":"10.1145","author":[{"given":"Guy","family":"Barshatski","sequence":"first","affiliation":[{"name":"Technion, Haifa, Israel"}]},{"given":"Kira","family":"Radinsky","sequence":"additional","affiliation":[{"name":"Technion, Haifa, Israel"}]}],"member":"320","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-015-0069-3"},{"key":"e_1_3_2_2_2_1","volume-title":"Quantifying the chemical beauty of drugs. Nature chemistry","author":"Bickerton Richard","year":"2012","unstructured":"Richard Bickerton , Gaia Paolini , J\u00e9r\u00e9my Besnard , Sorel Muresan , and Andrew Hopkins . 2012. Quantifying the chemical beauty of drugs. Nature chemistry , Vol. 4 (02 2012 ), 90--8. Richard Bickerton, Gaia Paolini, J\u00e9r\u00e9my Besnard, Sorel Muresan, and Andrew Hopkins. 2012. Quantifying the chemical beauty of drugs. Nature chemistry, Vol. 4 (02 2012), 90--8."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"volume-title":"Statistical Power Analysis for the Behavioral Sciences","author":"Cohen J.","key":"e_1_3_2_2_4_1","unstructured":"J. Cohen . 1988. Statistical Power Analysis for the Behavioral Sciences . Lawrence Erlbaum Associates . J. Cohen. 1988. Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates."},{"key":"e_1_3_2_2_5_1","volume-title":"Syntax-Directed Variational Autoencoder for Structured Data. In International Conference on Learning Representations .","author":"Dai Hanjun","year":"2018","unstructured":"Hanjun Dai , Yingtao Tian , Bo Dai , Steven Skiena , and Le Song . 2018 . Syntax-Directed Variational Autoencoder for Structured Data. In International Conference on Learning Representations . Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, and Le Song. 2018. Syntax-Directed Variational Autoencoder for Structured Data. In International Conference on Learning Representations ."},{"key":"e_1_3_2_2_6_1","volume-title":"CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. In 34th AAAI Conference on Artificial Intelligence (AAAI-20)","author":"Fu Tianfan","year":"2020","unstructured":"Tianfan Fu , Cao Xiao , and Jimeng Sun . 2020 . CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. In 34th AAAI Conference on Artificial Intelligence (AAAI-20) . Tianfan Fu, Cao Xiao, and Jimeng Sun. 2020. CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. In 34th AAAI Conference on Artificial Intelligence (AAAI-20) ."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1021\/acscentsci.7b00572"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219882"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/3157096.3157188"},{"key":"e_1_3_2_2_10_1","volume-title":"Junction Tree Variational Autoencoder for Molecular Graph Generation. In International Conference on Machine Learning. 2323--2332","author":"Jin Wengong","year":"2018","unstructured":"Wengong Jin , Regina Barzilay , and Tommi Jaakkola . 2018 . Junction Tree Variational Autoencoder for Molecular Graph Generation. In International Conference on Machine Learning. 2323--2332 . Wengong Jin, Regina Barzilay, and Tommi Jaakkola. 2018. Junction Tree Variational Autoencoder for Molecular Graph Generation. In International Conference on Machine Learning. 2323--2332."},{"key":"e_1_3_2_2_11_1","volume-title":"Learning Multimodal Graph-to-Graph Translation for Molecule Optimization. In International Conference on Learning Representations .","author":"Jin Wengong","year":"2019","unstructured":"Wengong Jin , Kevin Yang , Regina Barzilay , and Tommi Jaakkola . 2019 . Learning Multimodal Graph-to-Graph Translation for Molecule Optimization. In International Conference on Learning Representations . Wengong Jin, Kevin Yang, Regina Barzilay, and Tommi Jaakkola. 2019. Learning Multimodal Graph-to-Graph Translation for Molecule Optimization. In International Conference on Learning Representations ."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_43"},{"volume-title":"Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings .","author":"Diederik","key":"e_1_3_2_2_13_1","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015 . Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings . Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings ."},{"key":"e_1_3_2_2_14_1","volume-title":"Kingma and Max Welling","author":"Diederik","year":"2014","unstructured":"Diederik P. Kingma and Max Welling . 2014 . Auto-Encoding Variational Bayes.. In ICLR, Yoshua Bengio and Yann LeCun (Eds .). Diederik P. Kingma and Max Welling. 2014. Auto-Encoding Variational Bayes.. In ICLR, Yoshua Bengio and Yann LeCun (Eds.)."},{"key":"e_1_3_2_2_15_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning -","volume":"70","author":"Kusner Matt J.","year":"2017","unstructured":"Matt J. Kusner , Brooks Paige , and Jos\u00e9 Miguel Hern\u00e1ndez-Lobato . 2017 . Grammar Variational Autoencoder . In Proceedings of the 34th International Conference on Machine Learning - Volume 70 (Sydney, NSW, Australia) (ICML'17). 1945--1954. Matt J. Kusner, Brooks Paige, and Jos\u00e9 Miguel Hern\u00e1ndez-Lobato. 2017. Grammar Variational Autoencoder. In Proceedings of the 34th International Conference on Machine Learning - Volume 70 (Sydney, NSW, Australia) (ICML'17). 1945--1954."},{"key":"e_1_3_2_2_16_1","volume-title":"Rdkit: Open-source cheminformatics software.","author":"Landrum G","year":"2016","unstructured":"G Landrum . 2016 . Rdkit: Open-source cheminformatics software. G Landrum. 2016. Rdkit: Open-source cheminformatics software."},{"key":"e_1_3_2_2_17_1","volume-title":"Decoupled Weight Decay Regularization. In International Conference on Learning Representations .","author":"Loshchilov Ilya","year":"2019","unstructured":"Ilya Loshchilov and Frank Hutter . 2019 . Decoupled Weight Decay Regularization. In International Conference on Learning Representations . Ilya Loshchilov and Frank Hutter. 2019. Decoupled Weight Decay Regularization. In International Conference on Learning Representations ."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-019-0404-1"},{"key":"e_1_3_2_2_19_1","volume-title":"World Health Organization model list of essential medicines: 21st list","author":"World Health Organization","year":"2019","unstructured":"World Health Organization . 2019. World Health Organization model list of essential medicines: 21st list 2019 . Technical documents. 60 p. pages. World Health Organization. 2019. World Health Organization model list of essential medicines: 21st list 2019. Technical documents. 60 p. pages."},{"key":"e_1_3_2_2_20_1","first-page":"8026","article-title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","volume":"32","author":"Paszke Adam","year":"2019","unstructured":"Adam Paszke , Sam Gross , Francisco Massa , Adam Lerer , James Bradbury , Gregory Chanan , Trevor Killeen , Zeming Lin , Natalia Gimelshein , Luca Antiga , Alban Desmaison , Andreas Kopf , Edward Yang , Zachary DeVito , Martin Raison , Alykhan Tejani , Sasank Chilamkurthy , Benoit Steiner , Lu Fang , Junjie Bai , and Soumith Chintala . 2019 . PyTorch: An Imperative Style, High-Performance Deep Learning Library . In Advances in Neural Information Processing Systems 32. 8026 -- 8037 . Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32. 8026--8037.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10822-013-9672-4"},{"key":"e_1_3_2_2_22_1","volume-title":"4th International Conference on Learning Representations, ICLR","author":"Radford Alec","year":"2016","unstructured":"Alec Radford , Luke Metz , and Soumith Chintala . 2016. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks . In 4th International Conference on Learning Representations, ICLR 2016 , San Juan, Puerto Rico , May 2--4, 2016, Conference Track Proceedings . Alec Radford, Luke Metz, and Soumith Chintala. 2016. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. In 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2--4, 2016, Conference Track Proceedings ."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci100050t"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.22237\/jmasm\/1257035100"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41573-019-0017-4"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.4300\/JGME-D-12-00156.1"},{"key":"e_1_3_2_2_27_1","volume-title":"Nature","volume":"555","author":"Wang Sheng","year":"2018","unstructured":"Sheng Wang , Tao Che , Anat Levit , Brian Shoichet , Daniel Wacker , and Bryan Roth . 2018 . Structure of the D2 dopamine receptor bound to the atypical antipsychotic drug risperidone . Nature , Vol. 555 (03 2018), 269--273. Sheng Wang, Tao Che, Anat Levit, Brian Shoichet, Daniel Wacker, and Bryan Roth. 2018. Structure of the D2 dopamine receptor bound to the atypical antipsychotic drug risperidone. Nature, Vol. 555 (03 2018), 269--273."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci00057a005"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.2.270"},{"key":"e_1_3_2_2_30_1","volume-title":"Savita Shrivastava, Murtaza Hassanali, Paul Stothard, Zhan Chang, and Jennifer Woolsey.","author":"Wishart David S","year":"2006","unstructured":"David S Wishart , Craig Knox , An Chi Guo , Savita Shrivastava, Murtaza Hassanali, Paul Stothard, Zhan Chang, and Jennifer Woolsey. 2006 . DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic acids research, Vol. 34 , suppl_1 (2006), D668--D672. David S Wishart, Craig Knox, An Chi Guo, Savita Shrivastava, Murtaza Hassanali, Paul Stothard, Zhan Chang, and Jennifer Woolsey. 2006. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic acids research, Vol. 34, suppl_1 (2006), D668--D672."},{"volume-title":"Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. In 2017 IEEE International Conference on Computer Vision (ICCV). 2242--2251","author":"Zhu J.","key":"e_1_3_2_2_31_1","unstructured":"J. Zhu , T. Park , P. Isola , and A. A. Efros . 2017 . Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. In 2017 IEEE International Conference on Computer Vision (ICCV). 2242--2251 . J. Zhu, T. Park, P. Isola, and A. A. Efros. 2017. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. In 2017 IEEE International Conference on Computer Vision (ICCV). 2242--2251."}],"event":{"name":"KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Virtual Event Singapore","acronym":"KDD '21"},"container-title":["Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467120","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447548.3467120","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:26Z","timestamp":1750191506000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467120"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,14]]},"references-count":31,"alternative-id":["10.1145\/3447548.3467120","10.1145\/3447548"],"URL":"https:\/\/doi.org\/10.1145\/3447548.3467120","relation":{},"subject":[],"published":{"date-parts":[[2021,8,14]]},"assertion":[{"value":"2021-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}