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Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and drug manufacturing access to poorly available and brand-new molecules.
Learning to make generalizable and diverse predictions for retrosynthesis (2019)
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Coley, C. W., Rogers, L., Green, W. H. & Jensen, K. F · 2017
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Forward reaction prediction as reverse verification: A novel approach to retrosynthesis
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Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy
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Jin, W., Coley, C. W., Barzilay, R. & Jaakkola, T · 2017
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Deep learning based regression and multiclass models for acute oral toxicity prediction with automatic chemical feature extraction
Xu, Y., Pei, J. & Lai, L · 2017
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Organic synthesis provides opportunities to transform drug discovery
Blakemore, D. C. et al · 2018
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Computational chemical synthesis analysis and pathway design
Feng, F., Lai, L. & Pei, J · 2018
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The rise of deep learning in drug discovery
Chen, H., Engkvist, O., Wang, Y., Olivecrona, M. & Blaschke, T · 2018
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Planning chemical syntheses with deep neural networks and symbolic ai
Segler, M. H., Preuss, M. & Waller, M. P · 2018
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Modeling relational data with graph convolutional networks
Schlichtkrull, M. et al · 2018
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Schwaller, P. et al · 2020
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Levenshtein augmentation improves performance of smiles based deep-learning synthesis prediction
Sumner, D., He, J., Thakkar, A., Engkvist, O. & Bjerrum, E. J · 2020
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Aizynthfinder: a fast, robust and flexible open-source software for retrosynthetic planning
Genheden, S. et al · 2020
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Zinc20—a free ultralarge-scale chemical database for ligand discovery
Irwin, J. J. et al · 2020
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An extended overview of the clef 2020 chemu lab: information extraction of chemical reactions from patents
He, J. et al · 2020
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Overview of chemu 2020: named entity recognition and event extraction of chemical reactions from patents
He, J. et al · 2020
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Computational planning of the synthesis of complex natural products
Mikulak-Klucznik, B. et al · 2020
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Retcl: A selection-based approach for retrosynthesis via contrastive learning
Lee, H. et al · 2021
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Deep retrosynthetic reaction prediction using local reactivity and global attention
Chen, S. & Jung, Y · 2021
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Retroprime: A diverse, plausible and transformer-based method for single-step retrosynthesis predictions
Wang, X. et al · 2021
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Learning graph models for retrosynthesis prediction
Somnath, V. R., Bunne, C., Coley, C. W., Krause, A. & Barzilay, R · 2021
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Gta: Graph truncated attention for retrosynthesis
Seo, S.-W. et al · 2021
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Valid, plausible, and diverse retrosynthesis using tied two-way transformers with latent variables
Kim, E., Lee, D., Kwon, Y., Park, M. S. & Choi, Y.-S · 2021
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Molecule edit graph attention network: modeling chemical reactions as sequences of graph edits
Sacha, M. et al · 2021
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Molecular graph enhanced transformer for retrosynthesis prediction
Mao, K. et al · 2021
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Retrosynthesis prediction using grammar-based neural machine translation: An information-theoretic approach
Mann, V. & Venkatasubramanian, V · 2021
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Substructure-based neural machine translation for retrosynthetic prediction
Ucak, U. V., Kang, T., Ko, J. & Lee, J · 2021
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Knowledge graph embedding for link prediction: A comparative analysis
Rossi, A., Barbosa, D., Firmani, D., Matinata, A. & Merialdo, P · 2021
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X-mol: large-scale pre-training for molecular understanding and diverse molecular analysis
Xue, D. et al · 2021
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Self-improved retrosynthetic planning
Kim, J., Ahn, S., Lee, H. & Shin, J · 2021
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Mapping the space of chemical reactions using attention-based neural networks
Schwaller, P. et al · 2021
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Mining toxicity information from large amounts of toxicity data
Wu, Z. et al · 2021
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Improving few-and zero-shot reaction template prediction using modern hopfield networks
Seidl, P. et al · 2022
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Chemformer: a pre-trained transformer for computational chemistry
Irwin, R., Dimitriadis, S., He, J. & Bjerrum, E. J · 2022
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Root-aligned smiles: a tight representation for chemical reaction prediction
Zhong, Z. et al · 2022
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Retrosynthetic reaction pathway prediction through neural machine translation of atomic environments
Ucak, U. V., Ashyrmamatov, I., Ko, J. & Lee, J · 2022
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Ai-driven synthetic route design incorporated with retrosynthesis knowledge
Ishida, S., Terayama, K., Kojima, R., Takasu, K. & Okuno, Y · 2022
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Retrograph: Retrosynthetic planning with graph search
Xie, S. et al · 2022
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Paroutes: towards a framework for benchmarking retrosynthesis route predictions
Genheden, S. & Bjerrum, E · 2022
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Machine learning may sometimes simply capture literature popularity trends: A case study of heterocyclic suzuki–miyaura coupling
Beker, W. et al · 2022
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Explainable fragment-based molecular property attribution
Jia, L. et al · 2022
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