Dmytro Guzenko

4.5k total citations
15 papers, 370 citations indexed

About

Dmytro Guzenko is a scholar working on Molecular Biology, Cell Biology and Materials Chemistry. According to data from OpenAlex, Dmytro Guzenko has authored 15 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 3 papers in Cell Biology and 3 papers in Materials Chemistry. Recurrent topics in Dmytro Guzenko's work include Skin and Cellular Biology Research (3 papers), Protein Structure and Dynamics (3 papers) and Genomics and Phylogenetic Studies (3 papers). Dmytro Guzenko is often cited by papers focused on Skin and Cellular Biology Research (3 papers), Protein Structure and Dynamics (3 papers) and Genomics and Phylogenetic Studies (3 papers). Dmytro Guzenko collaborates with scholars based in Belgium, United States and Russia. Dmytro Guzenko's co-authors include Sergei V. Strelkov, A.A. Chernyatina, José M. Duarte, S.K. Burley, Kris Gevaert, Vasily N. Aushev, Peter Kalev, Michal Šimíček, Sam Lievens and Maria Francesca Baietti and has published in prestigious journals such as Bioinformatics, Nature Cell Biology and Scientific Reports.

In The Last Decade

Dmytro Guzenko

14 papers receiving 367 citations

Peers

Dmytro Guzenko
Dmytro Guzenko
Citations per year, relative to Dmytro Guzenko Dmytro Guzenko (= 1×) peers Kunihiko Yasuda

Countries citing papers authored by Dmytro Guzenko

Since Specialization
Citations

This map shows the geographic impact of Dmytro Guzenko'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 Dmytro Guzenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmytro Guzenko more than expected).

Fields of papers citing papers by Dmytro Guzenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dmytro Guzenko. 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 Dmytro Guzenko. The network helps show where Dmytro Guzenko may publish in the future.

Co-authorship network of co-authors of Dmytro Guzenko

This figure shows the co-authorship network connecting the top 25 collaborators of Dmytro Guzenko. A scholar is included among the top collaborators of Dmytro Guzenko based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dmytro Guzenko. Dmytro Guzenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Garcia‐Molina, Gary, et al.. (2025). Sleep and cardiorespiratory function assessed by a smart bed over 10 weeks post COVID-19 infection. Scientific Reports. 15(1). 2724–2724. 1 indexed citations
2.
Guzenko, Dmytro, et al.. (2024). Fine tuned personalized machine learning models to detect insomnia risk based on data from a smart bed platform. Frontiers in Neurology. 15. 1303978–1303978. 2 indexed citations
3.
Guzenko, Dmytro, et al.. (2023). 0368 Vulnerability to influenza-like illness is associated with insomnia severity. SLEEP. 46(Supplement_1). A163–A163. 1 indexed citations
5.
Guzenko, Dmytro, S.K. Burley, & José M. Duarte. (2020). Real time structural search of the Protein Data Bank. PLoS Computational Biology. 16(7). e1007970–e1007970. 40 indexed citations
6.
Hura, Greg L., Daniel J. Rosenberg, Dmytro Guzenko, et al.. (2019). Small angle X‐ray scattering‐assisted protein structure prediction in CASP13 and emergence of solution structure differences. Proteins Structure Function and Bioinformatics. 87(12). 1298–1314. 22 indexed citations
7.
Chernyatina, A.A., et al.. (2019). Lateral A11 type tetramerization in lamins. Journal of Structural Biology. 209(1). 107404–107404. 26 indexed citations
8.
Lafita, Aleix, Spencer Bliven, Andreas Prlić, et al.. (2019). BioJava 5: A community driven open-source bioinformatics library. PLoS Computational Biology. 15(2). e1006791–e1006791. 29 indexed citations
9.
Guzenko, Dmytro & Sergei V. Strelkov. (2018). Optimal data-driven parameterization of coiled coils. Journal of Structural Biology. 204(1). 125–129. 3 indexed citations
10.
Guzenko, Dmytro & Sergei V. Strelkov. (2017). CCFold: rapid and accurate prediction of coiled-coil structures and application to modelling intermediate filaments. Bioinformatics. 34(2). 215–222. 28 indexed citations
11.
Guzenko, Dmytro, A.A. Chernyatina, & Sergei V. Strelkov. (2017). Crystallographic Studies of Intermediate Filament Proteins. Sub-cellular biochemistry. 82. 151–170. 33 indexed citations
12.
Guzenko, Dmytro & Sergei V. Strelkov. (2016). Granular clustering of de novo protein models. Bioinformatics. 33(3). 390–396. 3 indexed citations
13.
Chernyatina, A.A., Dmytro Guzenko, & Sergei V. Strelkov. (2015). Intermediate filament structure: the bottom-up approach. Current Opinion in Cell Biology. 32. 65–72. 93 indexed citations
14.
Chernyatina, A.A., John F. Hess, Dmytro Guzenko, John C. Voss, & Sergei V. Strelkov. (2015). How to Study Intermediate Filaments in Atomic Detail. Methods in enzymology on CD-ROM/Methods in enzymology. 568. 3–33. 12 indexed citations
15.
Šimíček, Michal, Sam Lievens, Mathias Laga, et al.. (2013). The deubiquitylase USP33 discriminates between RALB functions in autophagy and innate immune response. Nature Cell Biology. 15(10). 1220–1230. 77 indexed citations

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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