| 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 | 986 | 2019 |
| Applications of deep learning in biomedicine P Mamoshina, A Vieira, E Putin, A Zhavoronkov Molecular pharmaceutics 13 (5), 1445-1454, 2016 | 767 | 2016 |
| Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data A Aliper, S Plis, A Artemov, A Ulloa, P Mamoshina, A Zhavoronkov Molecular pharmaceutics 13 (7), 2524-2530, 2016 | 574 | 2016 |
| druGAN: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico A Kadurin, S Nikolenko, K Khrabrov, A Aliper, A Zhavoronkov Molecular pharmaceutics 14 (9), 3098-3104, 2017 | 521 | 2017 |
| 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, 565644, 2020 | 512 | 2020 |
| The role of DNA damage and repair in aging through the prism of Koch-like criteria AA Moskalev, MV Shaposhnikov, EN Plyusnina, A Zhavoronkov, ... Ageing research reviews 12 (2), 661-684, 2013 | 484 | 2013 |
| 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 | 458 | 2018 |
| The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology A Kadurin, A Aliper, A Kazennov, P Mamoshina, Q Vanhaelen, ... Oncotarget 8 (7), 10883, 2017 | 377 | 2017 |
| Deep biomarkers of human aging: application of deep neural networks to biomarker development E Putin, P Mamoshina, A Aliper, M Korzinkin, A Moskalev, A Kolosov, ... Aging (albany NY) 8 (5), 1021, 2016 | 373 | 2016 |
| Reinforced Adversarial Neural Computer for de Novo Molecular Design E Putin, A Asadulaev, Y Ivanenkov, V Aladinskiy, B Sanchez-Lengeling, ... Journal of chemical information and modeling 58 (6), 1194-1204, 2018 | 365 | 2018 |
| Bifunctional immune checkpoint-targeted antibody-ligand traps that simultaneously disable TGFβ enhance the efficacy of cancer immunotherapy R Ravi, KA Noonan, V Pham, R Bedi, A Zhavoronkov, IV Ozerov, ... Nature communications 9 (1), 741, 2018 | 290 | 2018 |
| Potential non-covalent SARS-CoV-2 3C-like protease inhibitors designed using generative deep learning approaches and reviewed by human medicinal chemist in virtual reality A Zhavoronkov, B Zagribelnyy, A Zhebrak, V Aladinskiy, V Terentiev, ... | 250* | 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 | 242 | 2018 |
| Adversarial Threshold Neural Computer for Molecular de Novo Design E Putin, A Asadulaev, Q Vanhaelen, Y Ivanenkov, AV Aladinskaya, ... Molecular pharmaceutics 15 (10), 4386-4397, 2018 | 217 | 2018 |
| Genetics and epigenetics of aging and longevity A Moskalev, A Aliper, Z Smit-McBride, A Buzdin, A Zhavoronkov Cell Cycle 13 (7), 1063-1077, 2014 | 214 | 2014 |
| Brain-computer interface based on generation of visual images P Bobrov, A Frolov, C Cantor, I Fedulova, M Bakhnyan, A Zhavoronkov PloS one 6 (6), e20674, 2011 | 202 | 2011 |
| Human gut microbiome aging clock based on taxonomic profiling and deep learning F Galkin, P Mamoshina, A Aliper, E Putin, V Moskalev, VN Gladyshev, ... Iscience 23 (6), 2020 | 188* | 2020 |
| Machine learning on human muscle transcriptomic data for biomarker discovery and tissue-specific drug target identification P Mamoshina, M Volosnikova, IV Ozerov, E Putin, E Skibina, F Cortese, ... Frontiers in genetics 9, 242, 2018 | 185 | 2018 |
| Population specific biomarkers of human aging: a big data study using South Korean, Canadian, and Eastern European patient populations P Mamoshina, K Kochetov, E Putin, F Cortese, A Aliper, WS Lee, SM Ahn, ... The Journals of Gerontology: Series A 73 (11), 1482-1490, 2018 | 176 | 2018 |
| Artificial intelligence for aging and longevity research: Recent advances and perspectives A Zhavoronkov, P Mamoshina, Q Vanhaelen, M Scheibye-Knudsen, ... Ageing research reviews 49, 49-66, 2019 | 171 | 2019 |
Evgeny G IzumchenkoUniversity of Chicago在 uchicago.edu 的电子邮件经过验证
