Daniil Polykovskiy
Overview
Explore the profile of Daniil Polykovskiy including associated specialties, affiliations and a list of published articles.
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Articles
12
Citations
326
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Recent Articles
1.
Livne M, Miftahutdinov Z, Tutubalina E, Kuznetsov M, Polykovskiy D, Brundyn A, et al.
Chem Sci
. 2024 Jun;
15(22):8380-8389.
PMID: 38846388
Large Language Models (LLMs) have substantially driven scientific progress in various domains, and many papers have demonstrated their ability to tackle complex problems with creative solutions. Our paper introduces a...
2.
Kuznetsov M, Ryabov F, Schutski R, Shayakhmetov R, Lin Y, Aliper A, et al.
J Chem Inf Model
. 2024 Apr;
64(9):3610-3620.
PMID: 38668753
The fast and accurate conformation space modeling is an essential part of computational approaches for solving ligand and structure-based drug discovery problems. Recent state-of-the-art diffusion models for molecular conformation generation...
3.
Ren F, Aliper A, Chen J, Zhao H, Rao S, Kuppe C, et al.
Nat Biotechnol
. 2024 Mar;
43(1):63-75.
PMID: 38459338
Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at the clinical...
4.
Kamya P, Ozerov I, Pun F, Tretina K, Fokina T, Chen S, et al.
J Chem Inf Model
. 2024 Feb;
64(10):3961-3969.
PMID: 38404138
PandaOmics is a cloud-based software platform that applies artificial intelligence and bioinformatics techniques to multimodal omics and biomedical text data for therapeutic target and biomarker discovery. PandaOmics generates novel and...
5.
Aliper A, Kudrin R, Polykovskiy D, Kamya P, Tutubalina E, Chen S, et al.
Clin Pharmacol Ther
. 2023 Jul;
114(5):972-980.
PMID: 37483175
Drug discovery and development is a notoriously risky process with high failure rates at every stage, including disease modeling, target discovery, hit discovery, lead optimization, preclinical development, human safety, and...
6.
Pyrkov A, Aliper A, Bezrukov D, Lin Y, Polykovskiy D, Kamya P, et al.
Drug Discov Today
. 2023 Jun;
28(8):103675.
PMID: 37331692
In recent years, drug discovery and life sciences have been revolutionized with machine learning and artificial intelligence (AI) methods. Quantum computing is touted to be the next most significant leap...
7.
Ivanenkov Y, Polykovskiy D, Bezrukov D, Zagribelnyy B, Aladinskiy V, Kamya P, et al.
J Chem Inf Model
. 2023 Feb;
63(3):695-701.
PMID: 36728505
Chemistry42 is a software platform for small molecule design and optimization that integrates Artificial Intelligence (AI) techniques with computational and medicinal chemistry methodologies. Chemistry42 efficiently generates novel molecular structures with...
8.
Polykovskiy D, Zhebrak A, Sanchez-Lengeling B, Golovanov S, Tatanov O, Belyaev S, et al.
Front Pharmacol
. 2021 Jan;
11:565644.
PMID: 33390943
Generative models are becoming a tool of choice for exploring the molecular space. These models learn on a large training dataset and produce novel molecular structures with similar properties. Generated...
9.
Shayakhmetov R, Kuznetsov M, Zhebrak A, Kadurin A, Nikolenko S, Aliper A, et al.
Front Pharmacol
. 2020 Sep;
11:1236.
PMID: 32973498
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10.
Shayakhmetov R, Kuznetsov M, Zhebrak A, Kadurin A, Nikolenko S, Aliper A, et al.
Front Pharmacol
. 2020 May;
11:269.
PMID: 32362822
Gene expression profiles are useful for assessing the efficacy and side effects of drugs. In this paper, we propose a new generative model that infers drug molecules that could induce...