Daniil Polykovskiy

13 papers receiving 608 citations

Daniil Polykovskiy's Hit Papers

PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery 2024 · 77 citations
770+1+2Years since publication4080120

Peers

Daniil Polykovskiy
Comparison fields: 5 of 112
  • Computational Theory and Mathematics 353
  • Health Informatics 18
  • Biophysics 41
  • Materials Chemistry 239
  • Aging 8
Replace Kuzma Khrabrov with:
Kuzma Khrabrov Russia
Vladimir Aladinskiy Russia
Artur Kadurin Russia
Kaitlyn Gayvert United States
Jeff Blaney United States
Petrina Kamya Hong Kong
Jiangming Sun Sweden
Minjie Mou China
Fergus Imrie United Kingdom
Arijit Roy India
Daniil Polykovskiy relative to Kuzma Khrabrov Russia Kuzma Khrabrov's profile →
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Citations per year

Countries citing papers authored by Daniil Polykovskiy

Since Specialization
Citations

This map shows the geographic impact of Daniil Polykovskiy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniil Polykovskiy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniil Polykovskiy more than expected).

Fields of papers citing papers by Daniil Polykovskiy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniil Polykovskiy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniil Polykovskiy. The network helps show where Daniil Polykovskiy may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniil Polykovskiy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniil Polykovskiy Line = papers co-authored together Daniil Polykovskiy links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2018184
2
Chemistry42: An AI-Driven Platform for Molecular Design and Optimization
Hit paper breakdown →
2023124
3
PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery
Hit paper breakdown →
202477
4 201870
5 202354
6 202346
7 202129
8 202029
9 202426
10 20255
11
Extracting Invariant Features From Images Using An Equivariant Autoencoder.
20183
12 20242
13 20251
14
Concorde: Morphological Agreement in Conversational Models
20180

About Daniil Polykovskiy

Daniil Polykovskiy is a scholar working on Computational Theory and Mathematics, Molecular Biology, Materials Chemistry, Artificial Intelligence and Pharmacology, having authored 14 papers that have together received 650 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Machine Learning in Materials Science (6 papers), Topic Modeling (2 papers), Natural Language Processing Techniques (2 papers), Microbial Natural Products and Biosynthesis (1 paper), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Genetics, Bioinformatics, and Biomedical Research (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Computational Theory and Mathematics (353 citations), Health Informatics (18 citations), Biophysics (41 citations), Materials Chemistry (239 citations) and Aging (8 citations). Daniil Polykovskiy has collaborated with scholars based in Russia, United States and Hong Kong. Frequent co-authors include Alex Zhavoronkov, Alex Aliper, Yan A. Ivanenkov, Vladimir Aladinskiy, Alexander Zhebrak, Petrina Kamya, Feng Ren, Artur Kadurin, Alexander Aliper and Maksim Kuznetsov. Their work appears in journals such as Journal of Chemical Information and Modeling, Molecular Pharmaceutics, Drug Discovery Today, Clinical Pharmacology & Therapeutics and Frontiers in Pharmacology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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