182 related articles for article (PubMed ID: 34273053)
21. Modeling Physico-Chemical ADMET Endpoints with Multitask Graph Convolutional Networks.
Montanari F; Kuhnke L; Ter Laak A; Clevert DA
Molecules; 2019 Dec; 25(1):. PubMed ID: 31877719
[TBL] [Abstract][Full Text] [Related]
22. Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules.
Chung KC; Park H
J Comput Aided Mol Des; 2016 Nov; 30(11):1019-1033. PubMed ID: 27448686
[TBL] [Abstract][Full Text] [Related]
23. A blind SAMPL6 challenge: insight into the octanol-water partition coefficients of drug-like molecules via a DFT approach.
Arslan E; Findik BK; Aviyente V
J Comput Aided Mol Des; 2020 Apr; 34(4):463-470. PubMed ID: 31939104
[TBL] [Abstract][Full Text] [Related]
24. Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.
Işık M; Levorse D; Mobley DL; Rhodes T; Chodera JD
J Comput Aided Mol Des; 2020 Apr; 34(4):405-420. PubMed ID: 31858363
[TBL] [Abstract][Full Text] [Related]
25. Prediction of cyclohexane-water distribution coefficients with COSMO-RS on the SAMPL5 data set.
Klamt A; Eckert F; Reinisch J; Wichmann K
J Comput Aided Mol Des; 2016 Nov; 30(11):959-967. PubMed ID: 27460058
[TBL] [Abstract][Full Text] [Related]
26. Use of molecular dynamics fingerprints (MDFPs) in SAMPL6 octanol-water log P blind challenge.
Wang S; Riniker S
J Comput Aided Mol Des; 2020 Apr; 34(4):393-403. PubMed ID: 31745704
[TBL] [Abstract][Full Text] [Related]
27. Testing automatic methods to predict free binding energy of host-guest complexes in SAMPL7 challenge.
Serillon D; Bo C; Barril X
J Comput Aided Mol Des; 2021 Feb; 35(2):209-222. PubMed ID: 33464434
[TBL] [Abstract][Full Text] [Related]
28. Predicting Infrared Spectra with Message Passing Neural Networks.
McGill C; Forsuelo M; Guan Y; Green WH
J Chem Inf Model; 2021 Jun; 61(6):2594-2609. PubMed ID: 34048221
[TBL] [Abstract][Full Text] [Related]
29. Performance and robustness of small molecule retention time prediction with molecular graph neural networks in industrial drug discovery campaigns.
Vik D; Pii D; Mudaliar C; Nørregaard-Madsen M; Kontijevskis A
Sci Rep; 2024 Apr; 14(1):8733. PubMed ID: 38627535
[TBL] [Abstract][Full Text] [Related]
30. Predicting Critical Properties and Acentric Factors of Fluids Using Multitask Machine Learning.
Biswas S; Chung Y; Ramirez J; Wu H; Green WH
J Chem Inf Model; 2023 Aug; 63(15):4574-4588. PubMed ID: 37487557
[TBL] [Abstract][Full Text] [Related]
31. Prediction of the n-octanol/water partition coefficients in the SAMPL6 blind challenge from MST continuum solvation calculations.
Zamora WJ; Pinheiro S; German K; Ràfols C; Curutchet C; Luque FJ
J Comput Aided Mol Des; 2020 Apr; 34(4):443-451. PubMed ID: 31776809
[TBL] [Abstract][Full Text] [Related]
32. Multitask deep learning with dynamic task balancing for quantum mechanical properties prediction.
Yang Z; Zhong W; Lv Q; Chen CY
Phys Chem Chem Phys; 2022 Mar; 24(9):5383-5393. PubMed ID: 35169821
[TBL] [Abstract][Full Text] [Related]
33. Predicting Energetics Materials' Crystalline Density from Chemical Structure by Machine Learning.
Nguyen P; Loveland D; Kim JT; Karande P; Hiszpanski AM; Han TY
J Chem Inf Model; 2021 May; 61(5):2147-2158. PubMed ID: 33899482
[TBL] [Abstract][Full Text] [Related]
34. LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP.
Wang Y; Xiong J; Xiao F; Zhang W; Cheng K; Rao J; Niu B; Tong X; Qu N; Zhang R; Wang D; Chen K; Li X; Zheng M
J Cheminform; 2023 Sep; 15(1):76. PubMed ID: 37670374
[TBL] [Abstract][Full Text] [Related]
35. Prediction of n-octanol/water partition coefficients and acidity constants (pK
Viayna A; Pinheiro S; Curutchet C; Luque FJ; Zamora WJ
J Comput Aided Mol Des; 2021 Jul; 35(7):803-811. PubMed ID: 34244905
[TBL] [Abstract][Full Text] [Related]
36. Bioactivity Comparison across Multiple Machine Learning Algorithms Using over 5000 Datasets for Drug Discovery.
Lane TR; Foil DH; Minerali E; Urbina F; Zorn KM; Ekins S
Mol Pharm; 2021 Jan; 18(1):403-415. PubMed ID: 33325717
[TBL] [Abstract][Full Text] [Related]
37. Predicting partition coefficients of drug-like molecules in the SAMPL6 challenge with Drude polarizable force fields.
Ding Y; Xu Y; Qian C; Chen J; Zhu J; Huang H; Shi Y; Huang J
J Comput Aided Mol Des; 2020 Apr; 34(4):421-435. PubMed ID: 31960252
[TBL] [Abstract][Full Text] [Related]
38. Absolute and relative pK
Zeng Q; Jones MR; Brooks BR
J Comput Aided Mol Des; 2018 Oct; 32(10):1179-1189. PubMed ID: 30128926
[TBL] [Abstract][Full Text] [Related]
39. Multi-channel GCN ensembled machine learning model for molecular aqueous solubility prediction on a clean dataset.
Deng C; Liang L; Xing G; Hua Y; Lu T; Zhang Y; Chen Y; Liu H
Mol Divers; 2023 Jun; 27(3):1023-1035. PubMed ID: 35739374
[TBL] [Abstract][Full Text] [Related]
40. The SAMPL6 challenge on predicting aqueous pK
Tielker N; Eberlein L; Güssregen S; Kast SM
J Comput Aided Mol Des; 2018 Oct; 32(10):1151-1163. PubMed ID: 30073500
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]