| Deep learning enables rapid identification of potent DDR1 kinase inhibitors A Zhavoronkov, YA Ivanenkov, A Aliper, MS Veselov, VA Aladinskiy, ... Nature biotechnology 37 (9), 1038-1040, 2019 | 934 | 2019 |
| Molecular sets (MOSES): A benchmarking platform for molecular generation models D Polykovskiy, A Zhebrak, B Sanchez Lengeling, S Golovanov, O Tatanov, ... Frontiers in Pharmacology 11, 1931, 2020 | 553* | 2020 |
| Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare P Mamoshina, L Ojomoko, Y Yanovich, A Ostrovski, A Botezatu, ... Oncotarget 9 (5), 5665, 2018 | 442 | 2018 |
| Potential 2019-nCoV 3C-like protease inhibitors designed using generative deep learning approaches A Zhavoronkov, V Aladinskiy, A Zhebrak, B Zagribelnyy, V Terentiev, ... | 237* | 2020 |
| Entangled conditional adversarial autoencoder for de novo drug discovery D Polykovskiy, A Zhebrak, D Vetrov, Y Ivanenkov, V Aladinskiy, ... Molecular pharmaceutics 15 (10), 4398-4405, 2018 | 237 | 2018 |
| 3D molecular representations based on the wave transform for convolutional neural networks D Kuzminykh, D Polykovskiy, A Kadurin, A Zhebrak, I Baskov, S Nikolenko, ... Molecular pharmaceutics 15 (10), 4378-4385, 2018 | 113 | 2018 |
| Potential non-covalent SARS-CoV-2 3C-like protease inhibitors designed using generative deep learning approaches A Zhavoronkov, B Zagribelnyy, A Zhebrak, V Aladinskiy, V Terentiev, ... | 44 | 2020 |
| Molecular generation for desired transcriptome changes with adversarial autoencoders R Shayakhmetov, M Kuznetsov, A Zhebrak, A Kadurin, S Nikolenko, ... Frontiers in Pharmacology 11, 509129, 2020 | 29 | 2020 |
| A prior of a googol gaussians: a tensor ring induced prior for generative models M Kuznetsov, D Polykovskiy, D Vetrov, A Zhebrak 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019 | 19 | 2019 |
| Extracting invariant features from images using an equivariant autoencoder D Kuzminykh, D Polykovskiy, A Zhebrak Asian Conference on Machine Learning, 438-453, 2018 | 12 | 2018 |
| Chemistry42: An AI-based platform for de novo molecular design YA Ivanenkov, A Zhebrak, D Bezrukov, B Zagribelnyy, V Aladinskiy, ... arXiv preprint arXiv:2101.09050, 2021 | 4 | 2021 |
| Subset-Conditioned Generation Using Variational Autoencoder With A Learnable Tensor-Train Induced Prior M Kuznetsov, D Polykovskiy, D Vetrov, A Zhebrak Advances in Neural Information Processing Systems, Bayesian Deep Learning …, 2018 | 3 | 2018 |
| Subset conditioning using variational autoencoder with a learnable tensor train induced prior A Aliper, A Zavoronkovs, A Zhebrak, D Polykovskiy, M Kuznetsov, ... US Patent 11,893,498, 2024 | 1 | 2024 |
| Entangled conditional adversarial autoencoder for drug discovery D Polykovskiy, A Kadurin, AM Aliper, A Zhebrak, A Zavoronkovs US Patent App. 18/336,818, 2023 | | 2023 |
| Entangled conditional adversarial autoencoder for drug discovery D Polykovskiy, A Kadurin, AM Aliper, A Zhebrak, A Zavoronkovs US Patent 11,680,063, 2023 | | 2023 |
| Subset conditioning using variational autoencoder with a learnable tensor train induced prior A Aliper, A Zavoronkovs, A Zhebrak, D Polykovskiy, M Kuznetsov, ... US Patent 11,593,660, 2023 | | 2023 |
| Mutual information adversarial autoencoder A Aliper, A Zavoronkovs, A Zhebrak, A Kadurin, D Polykovskiy, ... US Patent App. 17/842,247, 2022 | | 2022 |
| APPLICATION OF ARTIFICIAL INTELLIGENCE TO PREDICT THE ECOTOXICOLOGICAL CHARACTERISTICS OF AVERMECTINS TVA AV, DA Polykovskiy, MD Kuznetsov, A Asadulaev, Y Volkov, A Zholus, ... identity 2, 134-153, 2012 | | 2012 |
| A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models (Supplementary) M Kuznetsov, D Polykovskiy, D Vetrov, A Zhebrak | | |
Daniil PolykovskiySr. Director of Technology, Insilico MedicineVerified email at insilico.com
