Artykuły udostępnione publicznie: - Thomas BlaschkeWięcej informacji
Dostępne w jakimś miejscu: 10
The rise of deep learning in drug discovery
H Chen, O Engkvist, Y Wang, M Olivecrona, T Blaschke
Drug discovery today 23 (6), 1241-1250, 2018
Upoważnienia: European Commission
Molecular de-novo design through deep reinforcement learning
M Olivecrona, T Blaschke, O Engkvist, H Chen
Journal of cheminformatics 9, 1-14, 2017
Upoważnienia: European Commission
Application of Generative Autoencoder in De Novo Molecular Design
T Blaschke, M Olivecrona, O Engkvist, J Bajorath, H Chen
Molecular informatics 37 (1-2), 1700123, 2018
Upoważnienia: European Commission
REINVENT 2.0: an AI tool for de novo drug design
T Blaschke, J Arús-Pous, H Chen, C Margreitter, C Tyrchan, O Engkvist, ...
Journal of chemical information and modeling 60 (12), 5918-5922, 2020
Upoważnienia: European Commission
Exploring the GDB-13 chemical space using deep generative models
J Arús-Pous, T Blaschke, S Ulander, JL Reymond, H Chen, O Engkvist
Journal of cheminformatics 11 (1), 1-14, 2019
Upoważnienia: European Commission
Memory-assisted reinforcement learning for diverse molecular de novo design
T Blaschke, O Engkvist, J Bajorath, H Chen
Journal of cheminformatics 12 (1), 68, 2020
Upoważnienia: European Commission
Prediction of different classes of promiscuous and nonpromiscuous compounds using machine learning and nearest neighbor analysis
T Blaschke, F Miljkovic, J Bajorath
ACS Omega 4 (4), 6883-6890, 2019
Upoważnienia: European Commission
Development of chromen-4-one derivatives as (ant) agonists for the lipid-activated G protein-coupled receptor GPR55 with tunable efficacy
CT Schoeder, A Meyer, AB Mahardhika, D Thimm, T Blaschke, M Funke, ...
ACS Omega 4 (2), 4276-4295, 2019
Upoważnienia: German Research Foundation, Federal Ministry of Education and Research, Germany
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES
EJ Bjerrum, C Margreitter, T Blaschke, S Kolarova, RLR de Castro
Journal of Computer-Aided Molecular Design 37 (8), 373-394, 2023
Upoważnienia: UK Biotechnology and Biological Sciences Research Council
An object-based semantic classification method of high resolution satellite imagery using ontology
HY Gu, HT Li, L Yan, T Blaschke
Upoważnienia: National Natural Science Foundation of China
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