Dmitry Suplatov

755 total citations
37 papers, 563 citations indexed

About

Dmitry Suplatov is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Dmitry Suplatov has authored 37 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 12 papers in Materials Chemistry and 6 papers in Computational Theory and Mathematics. Recurrent topics in Dmitry Suplatov's work include Protein Structure and Dynamics (17 papers), Enzyme Structure and Function (12 papers) and Microbial Metabolic Engineering and Bioproduction (9 papers). Dmitry Suplatov is often cited by papers focused on Protein Structure and Dynamics (17 papers), Enzyme Structure and Function (12 papers) and Microbial Metabolic Engineering and Bioproduction (9 papers). Dmitry Suplatov collaborates with scholars based in Russia, Tajikistan and Denmark. Dmitry Suplatov's co-authors include Vytas K. Švedas, Vladimir Voevodin, Evgeny Kirilin, Allan Svendsen, Vakil Takhaveev, Daria Timonina, Kateryna Fesko, Ekaterina Yu. Bezsudnova, Vladimir O. Popov and D. K. Nilov and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Dmitry Suplatov

35 papers receiving 545 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dmitry Suplatov Russia 16 464 135 64 63 60 37 563
Eva Šebestová Czechia 13 722 1.6× 180 1.3× 41 0.6× 45 0.7× 31 0.5× 14 861
Krishna Mohan Das India 10 377 0.8× 105 0.8× 55 0.9× 88 1.4× 245 4.1× 22 624
Tomáš Martínek Czechia 11 752 1.6× 81 0.6× 17 0.3× 27 0.4× 37 0.6× 22 917
Martin Maňák Czechia 5 301 0.6× 77 0.6× 22 0.3× 36 0.6× 34 0.6× 9 424
Scott C.‐H. Pegg United States 6 429 0.9× 113 0.8× 10 0.2× 48 0.8× 159 2.6× 8 557
Mitsuaki Sugahara Japan 13 586 1.3× 252 1.9× 78 1.2× 48 0.8× 21 0.3× 34 749
Adam Jurčík Czechia 6 253 0.5× 50 0.4× 13 0.2× 31 0.5× 29 0.5× 13 359
Ricardo Martí‐Arbona United States 9 378 0.8× 146 1.1× 44 0.7× 29 0.5× 64 1.1× 20 470
Ross Thyer United States 11 457 1.0× 52 0.4× 28 0.4× 56 0.9× 26 0.4× 16 628
Mason J. Appel United States 6 314 0.7× 48 0.4× 22 0.3× 69 1.1× 6 0.1× 9 425

Countries citing papers authored by Dmitry Suplatov

Since Specialization
Citations

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

Fields of papers citing papers by Dmitry Suplatov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dmitry Suplatov

This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Suplatov. A scholar is included among the top collaborators of Dmitry Suplatov 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 Dmitry Suplatov. Dmitry Suplatov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Suplatov, Dmitry, et al.. (2022). Loop 422–437 in NanA from Streptococcus pneumoniae plays the role of an active site lid and is associated with allosteric regulation. Computers in Biology and Medicine. 144. 105290–105290.
2.
Bezsudnova, Ekaterina Yu., A.Y. Nikolaeva, Tatiana V. Rakitina, et al.. (2021). Probing the role of the residues in the active site of the transaminase from Thermobaculum terrenum. PLoS ONE. 16(7). e0255098–e0255098. 2 indexed citations
3.
Timonina, Daria, et al.. (2021). Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies. Computational and Structural Biotechnology Journal. 19. 1302–1311. 9 indexed citations
4.
Suplatov, Dmitry, et al.. (2020). Mustguseal and Sister Web-Methods: A Practical Guide to Bioinformatic Analysis of Protein Superfamilies. Methods in molecular biology. 2231. 179–200. 5 indexed citations
5.
Suplatov, Dmitry, et al.. (2019). parMATT: parallel multiple alignment of protein 3D-structures with translations and twists for distributed-memory systems. Bioinformatics. 35(21). 4456–4458. 18 indexed citations
6.
Suplatov, Dmitry, et al.. (2019). Yosshi: a web-server for disulfide engineering by bioinformatic analysis of diverse protein families. Nucleic Acids Research. 47(W1). W308–W314. 18 indexed citations
7.
Suplatov, Dmitry, et al.. (2018). Human p38α mitogen-activated protein kinase in the Asp168-Phe169-Gly170-in (DFG-in) state can bind allosteric inhibitor Doramapimod. Journal of Biomolecular Structure and Dynamics. 37(8). 2049–2060. 15 indexed citations
8.
Bezsudnova, Ekaterina Yu., Konstantin M. Boyko, A.Y. Nikolaeva, et al.. (2018). Biochemical and structural insights into PLP fold type IV transaminase from Thermobaculum terrenum. Biochimie. 158. 130–138. 21 indexed citations
9.
Bezsudnova, Ekaterina Yu., et al.. (2016). Experimental and computational studies on the unusual substrate specificity of branched-chain amino acid aminotransferase from Thermoproteus uzoniensis. Archives of Biochemistry and Biophysics. 607. 27–36. 20 indexed citations
10.
Suplatov, Dmitry, et al.. (2016). Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer. Journal of Bioinformatics and Computational Biology. 14(2). 1641008–1641008. 8 indexed citations
11.
Suplatov, Dmitry & Vytas K. Švedas. (2015). Study of Functional and Allosteric Sites in Protein Superfamilies. Acta Naturae. 7(4). 34–54. 8 indexed citations
12.
Suplatov, Dmitry, et al.. (2014). Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions. PLoS ONE. 9(6). e100643–e100643. 59 indexed citations
13.
14.
Suplatov, Dmitry, Vladimir Voevodin, & Vytas K. Švedas. (2014). Robust enzyme design: Bioinformatic tools for improved protein stability. Biotechnology Journal. 10(3). 344–355. 58 indexed citations
15.
Suplatov, Dmitry & Vytas K. Švedas. (2013). Understanding structure-function relationship in protein families: bioinformatics and molecular modeling provide new concept for enzyme engineering. FEBS Journal. 280(1). 589. 2 indexed citations
16.
Suplatov, Dmitry, et al.. (2013). Bioinformatic analysis and molecular modeling reveal mutation bD484N to stabilize penicillin acylase and improve its catalytic performance in alkaline medium. FEBS Journal. 280(1). 614. 1 indexed citations
17.
Suplatov, Dmitry, Evgeny Kirilin, Vakil Takhaveev, & Vytas K. Švedas. (2013). Zebra: a web server for bioinformatic analysis of diverse protein families. Journal of Biomolecular Structure and Dynamics. 32(11). 1752–1758. 30 indexed citations
18.
Suplatov, Dmitry, et al.. (2013). Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity. Journal of Biomolecular Structure and Dynamics. 32(1). 75–87. 26 indexed citations
19.
Suplatov, Dmitry, et al.. (2012). Bioinformatic analysis of alpha/beta-hydrolase fold enzymes reveals subfamily-specific positions responsible for discrimination of amidase and lipase activities. Protein Engineering Design and Selection. 25(11). 689–697. 46 indexed citations
20.

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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