QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design-Reference-Cited by-同舟云学术

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QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design

Published:2024-07-01 Issue:14 Volume:64 Page:5365-5374
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Mervin Lewis¹^ORCID,Voronov Alexey²,Kabeshov Mikhail²^ORCID,Engkvist Ola²³^ORCID

Affiliation:

1. Molecular AI, Discovery Sciences, R&D, AstraZeneca, Cambridge CB2 0AA, United Kingdom

2. Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 412 96, Sweden

3. Department of Computer Science and Engineering, University of Gothenburg, Chalmers University of Technology, Gothenburg 412 96, Sweden

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00457

Reference74 articles.

1. Has Artificial Intelligence Impacted Drug Discovery?

2. Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges

3. Enhancing preclinical drug discovery with artificial intelligence

4. Prediction reliability of QSAR models: an overview of various validation tools

5. Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimal Molecular Design: Generative Active Learning Combining REINVENT with Precise Binding Free Energy Ranking Simulations;Journal of Chemical Theory and Computation;2024-09-03

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