Vladimir N. Uversky

107.5k total citations · 32 hit papers
1.1k papers, 73.4k citations indexed

About

Vladimir N. Uversky is a scholar working on Molecular Biology, Materials Chemistry and Physiology. According to data from OpenAlex, Vladimir N. Uversky has authored 1.1k papers receiving a total of 73.4k indexed citations (citations by other indexed papers that have themselves been cited), including 811 papers in Molecular Biology, 232 papers in Materials Chemistry and 144 papers in Physiology. Recurrent topics in Vladimir N. Uversky's work include Protein Structure and Dynamics (373 papers), Enzyme Structure and Function (213 papers) and RNA and protein synthesis mechanisms (124 papers). Vladimir N. Uversky is often cited by papers focused on Protein Structure and Dynamics (373 papers), Enzyme Structure and Function (213 papers) and RNA and protein synthesis mechanisms (124 papers). Vladimir N. Uversky collaborates with scholars based in United States, Russia and Saudi Arabia. Vladimir N. Uversky's co-authors include A. Keith Dunker, Anthony L. Fink, Christopher J. Oldfield, Bin Xue, Jie Li, Marc S. Cortese, J. R. Gillespie, Konstantin К. Turoverov, Irina М. Kuznetsova and Pedro Romero and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Vladimir N. Uversky

1.1k papers receiving 72.6k citations

Hit Papers

Why are ?natively unfolde... 1991 2026 2002 2014 2000 2014 2002 1991 2008 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Why are ?natively unfolded? proteins unstructured under physiologic conditions?
    2000 1.7k citations Vladimir N. Uversky, Anthony L. Fink et al. profile →
  2. Classification of Intrinsically Disordered Regions and Proteins
    2014 1.6k citations A. Keith Dunker, Vladimir N. Uversky et al. profile →
  3. Natively unfolded proteins: A point where biology waits for physics
    2002 1.4k citations Vladimir N. Uversky profile →
  4. Study of the “molten globule” intermediate state in protein folding by a hydrophobic fluorescent probe
    1991 1.1k citations Vladimir N. Uversky et al. profile →
  5. Intrinsically Disordered Proteins in Human Diseases: Introducing the D2Concept
    2008 1.1k citations Vladimir N. Uversky, A. Keith Dunker et al. profile →
  6. Effect of Environmental Factors on the Kinetics of Insulin Fibril Formation:  Elucidation of the Molecular Mechanism
    2001 1.0k citations Vladimir N. Uversky, Anthony L. Fink et al. profile →
  7. Understanding protein non-folding
    2010 969 citations Vladimir N. Uversky, A. Keith Dunker profile →
  8. PONDR-FIT: A meta-predictor of intrinsically disordered amino acids
    2010 950 citations A. Keith Dunker, Vladimir N. Uversky et al. profile →
  9. Flexible nets
    2005 913 citations A. Keith Dunker, Vladimir N. Uversky et al. profile →
  10. Evidence for a Partially Folded Intermediate in α-Synuclein Fibril Formation
    2001 909 citations Vladimir N. Uversky, Anthony L. Fink et al. profile →
  11. Metal-triggered Structural Transformations, Aggregation, and Fibrillation of Human α-Synuclein
    2001 892 citations Vladimir N. Uversky, Anthony L. Fink et al. profile →
  12. Conformational constraints for amyloid fibrillation: the importance of being unfolded
    2004 875 citations Vladimir N. Uversky, Anthony L. Fink profile →
  13. What does it mean to be natively unfolded?
    2002 805 citations Vladimir N. Uversky profile →
  14. Function and structure of inherently disordered proteins
    2008 775 citations A. Keith Dunker, Vladimir N. Uversky et al. profile →
  15. Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling
    2005 685 citations Vladimir N. Uversky, A. Keith Dunker et al. Journal of Molecular Recognition profile →
  16. DisProt: the Database of Disordered Proteins
    2006 651 citations Vladimir N. Uversky et al. profile →
  17. Analysis of Molecular Recognition Features (MoRFs)
    2006 597 citations Predrag Radivojac, A. Keith Dunker et al. profile →
  18. Intrinsic Disorder in Transcription Factors
    2006 592 citations Vladimir N. Uversky, A. Keith Dunker et al. profile →
  19. Introducing Protein Intrinsic Disorder
    2014 590 citations Vladimir N. Uversky et al. profile →
  20. Intrinsic Disorder and Functional Proteomics
    2006 572 citations Predrag Radivojac, Vladimir N. Uversky et al. profile →
  21. The unfoldomics decade: an update on intrinsically disordered proteins
    2008 548 citations A. Keith Dunker, Vladimir N. Uversky et al. profile →
  22. D2P2: database of disordered protein predictions
    2012 524 citations Vladimir N. Uversky, A. Keith Dunker et al. profile →
  23. Coupled Folding and Binding with α-Helix-Forming Molecular Recognition Elements
    2005 521 citations Vladimir N. Uversky, A. Keith Dunker et al. profile →
  24. α-Synuclein misfolding and Parkinson's disease
    2011 519 citations Vladimir N. Uversky et al. profile →
  25. The Herbicide Paraquat Causes Up-regulation and Aggregation of α-Synuclein in Mice
    2002 507 citations Vladimir N. Uversky, Anthony L. Fink et al. profile →
  26. Intrinsically disordered proteins in overcrowded milieu: Membrane-less organelles, phase separation, and intrinsic disorder
    2016 499 citations Vladimir N. Uversky profile →
  27. Encyclopedia of Metalloproteins
    2013 445 citations Vladimir N. Uversky et al. profile →
  28. Orderly order in protein intrinsic disorder distribution: disorder in 3500 proteomes from viruses and the three domains of life
    2012 439 citations A. Keith Dunker, Vladimir N. Uversky et al. profile →
  29. What Macromolecular Crowding Can Do to a Protein
    2014 433 citations Vladimir N. Uversky et al. International Journal of Molecular Sciences profile →
  30. Intrinsically Disordered Proteins and Their “Mysterious” (Meta)Physics
    2019 364 citations Vladimir N. Uversky profile →
  31. Bioactive Peptides: Synthesis, Sources, Applications, and Proposed Mechanisms of Action
    2022 359 citations Vladimir N. Uversky et al. International Journal of Molecular Sciences profile →
  32. Targeting autophagy in ischemic stroke: From molecular mechanisms to clinical therapeutics
    2021 220 citations Vladimir N. Uversky et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vladimir N. Uversky United States 132 51.9k 13.9k 10.8k 7.8k 7.2k 1.1k 73.4k
David Eisenberg United States 120 46.7k 0.9× 10.0k 0.7× 12.3k 1.1× 2.6k 0.3× 3.9k 0.5× 409 62.2k
Christopher M. Dobson United Kingdom 143 65.7k 1.3× 20.3k 1.5× 35.8k 3.3× 9.3k 1.2× 9.9k 1.4× 839 95.2k
Axel T. Brünger United States 103 42.9k 0.8× 12.3k 0.9× 2.7k 0.2× 1.7k 0.2× 12.5k 1.7× 298 56.0k
Michele Vendruscolo United Kingdom 98 29.6k 0.6× 8.1k 0.6× 13.9k 1.3× 4.9k 0.6× 4.1k 0.6× 570 41.7k
F. Ulrich Hartl Germany 122 45.6k 0.9× 8.8k 0.6× 4.0k 0.4× 1.6k 0.2× 10.0k 1.4× 284 53.2k
Susan Lindquist United States 125 44.9k 0.9× 4.1k 0.3× 7.3k 0.7× 4.7k 0.6× 8.1k 1.1× 301 56.5k
Ad Bax United States 131 61.5k 1.2× 18.6k 1.3× 3.7k 0.3× 2.0k 0.3× 6.0k 0.8× 464 89.2k
David S. Wishart Canada 112 48.3k 0.9× 4.9k 0.4× 6.1k 0.6× 1.0k 0.1× 2.4k 0.3× 553 75.7k
Roger Y. Tsien United States 151 70.9k 1.4× 8.0k 0.6× 8.1k 0.7× 870 0.1× 11.9k 1.7× 321 111.4k
Lewis C. Cantley United States 183 104.9k 2.0× 2.0k 0.1× 11.7k 1.1× 2.3k 0.3× 19.6k 2.7× 710 150.4k

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
1.
Nesterov, Semen V., Nikolay S. Ilyinsky, Alexander V. Fonin, & Vladimir N. Uversky. (2025). Signal Transduction by Phase Separation—Unnoticed Revolution in Molecular Biology. Journal of Molecular Recognition. 38(2). e70003–e70003. 1 indexed citations
2.
Dayhoff, Guy W., et al.. (2025). Proteome-wide identification and comprehensive profiling of intrinsic disorder in Fasciola gigantica. International Journal of Biological Macromolecules. 314. 144158–144158.
3.
Aljabali, Alaa A. A., Murtaza M. Tambuwala, Mohamed El‐Tanani, et al.. (2024). A comprehensive review of PRAME and BAP1 in melanoma: Genomic instability and immunotherapy targets. Cellular Signalling. 124. 111434–111434. 5 indexed citations
4.
El‐Maradny, Yousra A., et al.. (2024). Unraveling the role of the nucleocapsid protein in SARS-CoV-2 pathogenesis: From viral life cycle to vaccine development. International Journal of Biological Macromolecules. 279(Pt 2). 135201–135201. 7 indexed citations
5.
Uversky, Vladimir N., et al.. (2024). Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study. Computational Biology and Chemistry. 113. 108268–108268.
6.
Madeira, Pedro P., et al.. (2024). Correlation of Solvent Interaction Analysis Signatures with Thermodynamic Properties and In Silico Calculations of the Structural Effects of Point Mutations in Two Proteins. International Journal of Molecular Sciences. 25(17). 9652–9652. 2 indexed citations
7.
Uversky, Vladimir N., et al.. (2023). Intrinsic disorder may drive the interaction of PROS1 and MERTK in uveal melanoma. International Journal of Biological Macromolecules. 250. 126027–126027. 6 indexed citations
8.
Rubio‐Casillas, Alberto, et al.. (2023). Do vaccines increase or decrease susceptibility to diseases other than those they protect against?. Vaccine. 42(3). 426–440. 4 indexed citations
9.
Dayhoff, Guy W., et al.. (2023). Intrinsic disorder in PRAME and its role in uveal melanoma. Cell Communication and Signaling. 21(1). 222–222. 5 indexed citations
10.
Redwan, Elrashdy M., Alaa A. A. Aljabali, Wagner Baetas‐da‐Cruz, et al.. (2022). Would New SARS-CoV-2 Variants Change the War against COVID-19?. SHILAP Revista de lepidopterología. 3(2). 229–237. 2 indexed citations
11.
Kumar, Prateek, et al.. (2022). Role of structural disorder in the multi-functionality of flavivirus proteins. Expert Review of Proteomics. 19(3). 183–196. 2 indexed citations
12.
Uversky, Vladimir N., et al.. (2021). Understanding structural malleability of the SARS-CoV-2 proteins and relation to the comorbidities. Briefings in Bioinformatics. 22(6). 6 indexed citations
13.
Gutiérrez-Beltrán, Emilio, Pernilla H Elander, Kerstin Dalman, et al.. (2021). Tudor staphylococcal nuclease is a docking platform for stress granule components and is essential for SnRK1 activation in Arabidopsis. The EMBO Journal. 40(17). e105043–e105043. 57 indexed citations
14.
15.
Singh, Ankur, Ankur Kumar, Vladimir N. Uversky, & Rajanish Giri. (2018). Understanding the interactability of chikungunya virus proteinsviamolecular recognition feature analysis. RSC Advances. 8(48). 27293–27303. 29 indexed citations
16.
Abramov, Vyacheslav M., Vladimir L. Motin, В. С. Хлебников, et al.. (2018). Binding of LcrV protein from Yersinia pestis to human T-cells induces apoptosis, which is completely blocked by specific antibodies. International Journal of Biological Macromolecules. 122. 1062–1070. 7 indexed citations
17.
Pejaver, Vikas, Wei-Lun Hsu, A. Keith Dunker, Vladimir N. Uversky, & Predrag Radivojac. (2014). The structural and functional signatures of proteins that undergo multiple events of post-translational modification. PMC. 11 indexed citations
18.
Goh, Gerard Kian‐Meng, A. Keith Dunker, & Vladimir N. Uversky. (2009). Protein intrinsic disorder and influenza virulence: the 1918 H1N1 and H5N1 viruses. Publisher. 2 indexed citations
19.
Marsh, Joseph A., et al.. (2007). Synuclein-γ Targeting Peptide Inhibitor that Enhances Sensitivity of Breast Cancer Cells to Antimicrotubule Drugs. Cancer Research. 67(2). 626–633. 50 indexed citations
20.
Denning, Daniel P., Samir S. Patel, Vladimir N. Uversky, Anthony L. Fink, & Michael Rexach. (2003). Disorder in the nuclear pore complex: The FG repeat regions of nucleoporins are natively unfolded. Proceedings of the National Academy of Sciences. 100(5). 2450–2455. 389 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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