Vladimir N. Uversky

107.5k citations
1.1k papers · 73.4k indexed · 32 hit papers · h-index 132
Topics
Protein Structure and Dynamics (373 papers)Enzyme Structure and Function (213 papers)RNA and protein synthesis mechanisms (124 papers)

In The Last Decade

Vladimir N. Uversky

1.1k papers receiving 72.6k citations

Hit Papers

Why are?natively unfolded? proteins unstructured under ph...19912026200220142000201420021991200850010001.5k

Peers

Vladimir N. Uversky
Comparison fields: 5 of 212
  • Molecular Biology 51.9k
  • Materials Chemistry 13.9k
  • Physiology 10.8k
  • Neurology 7.8k
  • Cell Biology 7.2k
Replace Christopher M. Dobson with:
Christopher M. Dobson United Kingdom
David Eisenberg United States
Anthony L. Fink United States
Michele Vendruscolo United Kingdom
Tuomas P. J. Knowles United Kingdom
David S. Wishart Canada
Jeremy C. Smith United States
Ad Bax United States
Roger Y. Tsien United States
Axel T. Brünger United States
Vladimir N. Uversky relative to Christopher M. Dobson United Kingdom Christopher M. Dobson's profile →
Citations per field
00.5×1.5×
Christopher M. Dobson · 1×
Citations per year

Countries citing papers authored by Vladimir N. Uversky

Since Specialization
Citations

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

Fields of papers citing papers by Vladimir N. Uversky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vladimir N. Uversky. 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 Vladimir N. Uversky. The network helps show where Vladimir N. Uversky may publish in the future.

Co-authorship network of co-authors of Vladimir N. Uversky

This figure shows the co-authorship network connecting the top 25 collaborators of Vladimir N. Uversky. A scholar is included among the top collaborators of Vladimir N. Uversky 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 Vladimir N. Uversky. Vladimir N. Uversky 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
#WorkIndexed citations
1 0
2 5
3 7
4 0
5 4
6 6
7 4
8 5
9 4
10 4
11 6
12 0
13 5
14 7
15 11
16 6
17 57
18 0
19 50
20 389

About Vladimir N. Uversky

Vladimir N. Uversky is a scholar working on Filtration and Separation, Molecular Biology and Cell Biology, having authored 1.1k papers that have together received 73.4k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (373 papers), Enzyme Structure and Function (213 papers) and RNA and protein synthesis mechanisms (124 papers). The work is most often cited by research in Molecular Biology (51.9k citations), Neurology (7.8k citations) and Cell Biology (7.2k citations). Vladimir N. Uversky has collaborated with scholars based in United States, Russia and Saudi Arabia. Frequent co-authors include A. Keith Dunker, Anthony L. Fink, Christopher J. Oldfield, Bin Xue, Jie Li, Marc S. Cortese, J. R. Gillespie, Irina М. Kuznetsova, Konstantin К. Turoverov and Pedro Romero. Their work appears in journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

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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