Chemists: AI Is Here; Unite To Get the Benefits (Unknown)
- New search for: Griffen, Edward J.
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- https://orcid.org/0000-0003-0859-554X
- New search for: Dossetter, Alexander G.
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- https://orcid.org/0000-0002-4181-3193
- New search for: Leach, Andrew G.
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- https://orcid.org/0000-0003-1325-8273
- New search for: Griffen, Edward J.
- Further information on Griffen, Edward J.:
- https://orcid.org/0000-0003-0859-554X
- New search for: Dossetter, Alexander G.
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In:
Journal of Medicinal Chemistry
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63
, 16
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8695-8704
;
2020
- Article (Journal) / Electronic Resource
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Title:Chemists: AI Is Here; Unite To Get the Benefits
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Additional title:J. Med. Chem.
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Contributors:
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Published in:Journal of Medicinal Chemistry ; 63, 16 ; 8695-8704
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Publisher:
- New search for: American Chemical Society
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Publication date:2020-08-27
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ISSN:
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Coden:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:Unknown
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Source:
Table of contents – Volume 63, Issue 16
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 8651
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Artificial Intelligence in Drug Discovery: Into the Great Wide OpenBajorath, Jürgen / Kearnes, Steven / Walters, W. Patrick / Meanwell, Nicholas A. / Georg, Gunda I. / Wang, Shaomeng et al. | 2020
- 8653
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Drug Research Meets Network Science: Where Are We?Recanatini, Maurizio / Cabrelle, Chiara et al. | 2020
- 8667
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Current and Future Roles of Artificial Intelligence in Medicinal Chemistry SynthesisStruble, Thomas J. / Alvarez, Juan C. / Brown, Scott P. / Chytil, Milan / Cisar, Justin / DesJarlais, Renee L. / Engkvist, Ola / Frank, Scott A. / Greve, Daniel R. / Griffin, Daniel J. et al. | 2020
- 8683
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Transfer Learning for Drug DiscoveryCai, Chenjing / Wang, Shiwei / Xu, Youjun / Zhang, Weilin / Tang, Ke / Ouyang, Qi / Lai, Luhua / Pei, Jianfeng et al. | 2020
- 8695
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Chemists: AI Is Here; Unite To Get the BenefitsGriffen, Edward J. / Dossetter, Alexander G. / Leach, Andrew G. et al. | 2020
- 8705
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Learning Molecular Representations for Medicinal ChemistryChuang, Kangway V. / Gunsalus, Laura M. / Keiser, Michael J. et al. | 2020
- 8723
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Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment ValidationLi, Xutong / Li, Zhaojun / Wu, Xiaolong / Xiong, Zhaoping / Yang, Tianbiao / Fu, Zunyun / Liu, Xiaohong / Tan, Xiaoqin / Zhong, Feisheng / Wan, Xiaozhe et al. | 2020
- 8738
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Machine Learning Models for Accurate Prediction of Kinase Inhibitors with Different Binding ModesMiljković, Filip / Rodríguez-Pérez, Raquel / Bajorath, Jürgen et al. | 2020
- 8749
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Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention MechanismXiong, Zhaoping / Wang, Dingyan / Liu, Xiaohong / Zhong, Feisheng / Wan, Xiaozhe / Li, Xutong / Li, Zhaojun / Luo, Xiaomin / Chen, Kaixian / Jiang, Hualiang et al. | 2020
- 8761
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Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley ValuesRodríguez-Pérez, Raquel / Bajorath, Jürgen et al. | 2020
- 8778
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Practical High-Quality Electrostatic Potential Surfaces for Drug Discovery Using a Graph-Convolutional Deep Neural NetworkRathi, Prakash Chandra / Ludlow, R. Frederick / Verdonk, Marcel L. et al. | 2020
- 8791
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“Ring Breaker”: Neural Network Driven Synthesis Prediction of the Ring System Chemical SpaceThakkar, Amol / Selmi, Nidhal / Reymond, Jean-Louis / Engkvist, Ola / Bjerrum, Esben Jannik et al. | 2020
- 8809
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Automated De Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn?Grebner, Christoph / Matter, Hans / Plowright, Alleyn T. / Hessler, Gerhard et al. | 2020
- 8824
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An Artificial Intelligence Approach to Proactively Inspire Drug Discovery with RecommendationsRohall, Steven L. / Auch, Lydia / Gable, Jonathan / Gora, Jacob / Jansen, Johanna / Lu, Yipin / Martin, Eric / Pancost-Heidebrecht, Margaret / Shirley, Bill / Stiefl, Nikolaus et al. | 2020
- 8835
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Improvement in ADMET Prediction with Multitask Deep FeaturizationFeinberg, Evan N. / Joshi, Elizabeth / Pande, Vijay S. / Cheng, Alan C. et al. | 2020
- 8849
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Machine Learning in Mass Spectrometry: A MALDI-TOF MS Approach to Phenotypic Antibacterial Screeningvan Oosten, Luuk N. / Klein, Christian D. et al. | 2020
- 8857
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Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit FindingMcCloskey, Kevin / Sigel, Eric A. / Kearnes, Steven / Xue, Ling / Tian, Xia / Moccia, Dennis / Gikunju, Diana / Bazzaz, Sana / Chan, Betty / Clark, Matthew A. et al. | 2020
- 8867
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Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural NetworkStecula, Adrian / Hussain, Muhammad S. / Viola, Ronald E. et al. | 2020