Daniil Polykovskiy

About

Daniil Polykovskiy is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Daniil Polykovskiy has authored 13 papers receiving a total of 799 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Theory and Mathematics, 5 papers in Molecular Biology and 5 papers in Materials Chemistry. Recurrent topics in Daniil Polykovskiy’s work include Computational Drug Discovery Methods (8 papers), Machine Learning in Materials Science (5 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Daniil Polykovskiy is often cited by papers focused on Computational Drug Discovery Methods (8 papers), Machine Learning in Materials Science (5 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Daniil Polykovskiy collaborates with scholars based in United States, Russia and Hong Kong. Daniil Polykovskiy's co-authors include Alex Zhavoronkov, Artur Kadurin, Vladimir Aladinskiy, Alexander Zhebrak, Sergey Nikolenko, Yan A. Ivanenkov, Alán Aspuru‐Guzik, Simon Johansson, Mark S. Veselov and Sergey Golovanov and has published in prestigious journals such as Chemical Science, Clinical Pharmacology & Therapeutics and Drug Discovery Today.

In The Last Decade

Co-authorship network of co-authors of Daniil Polykovskiy i

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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.

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).

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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