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For: Mervin LH, Johansson S, Semenova E, Giblin KA, Engkvist O. Uncertainty quantification in drug design. Drug Discov Today 2021;26:474-89. [PMID: 33253918 DOI: 10.1016/j.drudis.2020.11.027] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Martinelli DD. Generative machine learning for de novo drug discovery: A systematic review. Comput Biol Med 2022;145:105403. [PMID: 35339849 DOI: 10.1016/j.compbiomed.2022.105403] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
2 Mervin LH, Trapotsi MA, Afzal AM, Barrett IP, Bender A, Engkvist O. Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty. J Cheminform 2021;13:62. [PMID: 34412708 DOI: 10.1186/s13321-021-00539-7] [Reference Citation Analysis]
3 Wang D, Yu J, Chen L, Li X, Jiang H, Chen K, Zheng M, Luo X. A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling. J Cheminform 2021;13:69. [PMID: 34544485 DOI: 10.1186/s13321-021-00551-x] [Reference Citation Analysis]
4 Obrezanova O, Martinsson A, Whitehead T, Mahmoud S, Bender A, Miljković F, Grabowski P, Irwin B, Oprisiu I, Conduit G, Segall M, Smith GF, Williamson B, Winiwarter S, Greene N. Prediction of In Vivo Pharmacokinetic Parameters and Time-Exposure Curves in Rats Using Machine Learning from the Chemical Structure. Mol Pharm 2022. [PMID: 35412314 DOI: 10.1021/acs.molpharmaceut.2c00027] [Reference Citation Analysis]
5 Norinder U, Spjuth O, Svensson F. Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning. J Cheminform 2021;13:77. [PMID: 34600569 DOI: 10.1186/s13321-021-00555-7] [Reference Citation Analysis]
6 Miljković F, Rodríguez-Pérez R, Bajorath J. Impact of Artificial Intelligence on Compound Discovery, Design, and Synthesis. ACS Omega 2021;6:33293-9. [PMID: 34926881 DOI: 10.1021/acsomega.1c05512] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]