Vladimir Aladinskiy
Insilicos (United States)(US)
Publications by Year
Research Areas
Computational Drug Discovery Methods, Machine Learning in Materials Science, Hepatitis C virus research, Synthesis and biological activity, Crystallization and Solubility Studies
Most-Cited Works
- → Deep learning enables rapid identification of potent DDR1 kinase inhibitors(2019)1,401 cited
- → Reinforced Adversarial Neural Computer for de Novo Molecular Design(2018)386 cited
- → AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor(2023)301 cited
- → Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery(2018)280 cited
- → A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models(2024)237 cited
- → Chemistry42: An AI-Driven Platform for Molecular Design and Optimization(2023)182 cited
- → Are We Opening the Door to a New Era of Medicinal Chemistry or Being Collapsed to a Chemical Singularity?(2019)115 cited
- → Potential 2019-nCoV 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches(2020)105 cited
- → Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches(2020)97 cited
- → Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models(2020)84 cited