Vasily M. Studitsky

7.2k total citations · 2 hit papers
150 papers, 5.5k citations indexed

About

Vasily M. Studitsky is a scholar working on Molecular Biology, Oncology and Plant Science. According to data from OpenAlex, Vasily M. Studitsky has authored 150 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 142 papers in Molecular Biology, 22 papers in Oncology and 12 papers in Plant Science. Recurrent topics in Vasily M. Studitsky's work include Genomics and Chromatin Dynamics (104 papers), RNA and protein synthesis mechanisms (56 papers) and RNA Research and Splicing (52 papers). Vasily M. Studitsky is often cited by papers focused on Genomics and Chromatin Dynamics (104 papers), RNA and protein synthesis mechanisms (56 papers) and RNA Research and Splicing (52 papers). Vasily M. Studitsky collaborates with scholars based in United States, Russia and Tajikistan. Vasily M. Studitsky's co-authors include Olga I. Kulaeva, Gary Felsenfeld, V. A. Bondarenko, David J. Clark, Danny Reinberg, Wendy Walter, Daria A. Gaykalova, Sangtaek Oh, Rimma Belotserkovskaya and George M. Orphanides and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Vasily M. Studitsky

142 papers receiving 5.4k citations

Hit Papers

align trajectories

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.

FACT Facilitates Transcription-Dependent Nucleosome Alteration

2003 691 citations Vasily M. Studitsky et al. profile →
ADAR1 masks the cancer immunotherapeutic promise of ZBP1-driven necroptosis

2022 262 citations Ting Zhang, Chaoran Yin et al. Nature profile →

Peers

Vasily M. Studitsky

MB

PS

GENET

ONCOL

IMMUN

Kyle M. Miller United States

Albino Bacolla United States

Alain Verreault Canada

Juergen Bode Germany

Heinz‐Peter Nasheuer Ireland

Nina C. Hubner Germany

Yuliang Wu Canada

Ann L. Beyer United States

Helen R. Flynn United Kingdom

Emmanuel Skordalakes United States

Kyle M. Miller United States

Vasily M. Studitsky

5.7k ×1.1

MB

479 ×0.8

PS

418 ×1.0

GENET

1.1k ×3.1

ONCOL

209 ×0.8

IMMUN

Citations per year, relative to Vasily M. Studitsky Vasily M. Studitsky (= 1×) peers Kyle M. Miller

Countries citing papers authored by Vasily M. Studitsky

Since Specialization

Citations

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

Fields of papers citing papers by Vasily M. Studitsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vasily M. Studitsky. 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 Vasily M. Studitsky. The network helps show where Vasily M. Studitsky may publish in the future.

Co-authorship network of co-authors of Vasily M. Studitsky

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Studitsky, Vasily M., et al.. (2025). Beyond Chaperoning: The Multifaceted Role of FACT in Chromatin Transactions. International Journal of Molecular Sciences. 26(11). 5176–5176. 1 indexed citations

2.

Armeev, Grigoriy A., Andrey Moiseenko, Леи Жао, et al.. (2025). Structure and dynamics of a nucleosome core particle based on Widom 603 DNA sequence. Structure. 33(5). 948–959.e5.

3.

Shi, Xiangyan, Elena Kotova, Grigoriy A. Armeev, et al.. (2025). Histone tetrasome dynamics affects chromatin transcription. Nucleic Acids Research. 53(8).

4.

Андреева, Т. В., et al.. (2024). Influence of Genistein on the Structure of Nucleosomes and Formation of Complexes With PARP1. Биофизика. 69(3). 432–443. 1 indexed citations

5.

Kumar, Ashutosh, et al.. (2023). The Ser7 of RNA Pol II-CTD influences the recruitment of Cdc73 for mRNA transcription. International Journal of Biological Macromolecules. 254(Pt 2). 127881–127881. 1 indexed citations

6.

Андреева, Т. В., et al.. (2023). On the interaction of resveratrol with nucleosomes. Биофизика. 68(3). 466–473. 1 indexed citations

7.

Belitsky, Gennady A., et al.. (2023). Mechanisms of action of plant polyphenols on the initiation of carcinogenesis. SHILAP Revista de lepidopterología. 10(2). 30–41.

8.

Герасимова, Н. С., Maaz Akhtar, & Vasily M. Studitsky. (2023). Effect of single-strand DNA breaks on transcription of nucleosomes. 77(4). 241–247. 1 indexed citations

9.

Studitsky, Vasily M., et al.. (2023). The Role of the WGR Domain in the Functions of PARP1 and PARP2. Молекулярная биология. 57(5). 782–791. 1 indexed citations

10.

Valieva, Maria E., Laura McCullough, Tim Formosa, et al.. (2022). Electron microscopy analysis of ATP-independent nucleosome unfolding by FACT. Communications Biology. 5(1). 2–2. 18 indexed citations

11.

Герасимова, Н. С., et al.. (2022). Structure of an Intranucleosomal DNA Loop That Senses DNA Damage during Transcription. Cells. 11(17). 2678–2678. 8 indexed citations

12.

Zhang, Ting, Chaoran Yin, А. И. Федоров, et al.. (2022). ADAR1 masks the cancer immunotherapeutic promise of ZBP1-driven necroptosis. Nature. 606(7914). 594–602. 262 indexed citations breakdown →

13.

Valieva, Maria E., et al.. (2018). HMGB-белки как ДНК-шапероны, модулирующие активность хроматина. Молекулярная биология. 52(5). 737–749. 13 indexed citations

14.

Studitsky, Vasily M., et al.. (2016). Структурные исследования факторов ремоделирования хроматина. Молекулярная биология. 50(6). 922–934. 2 indexed citations

15.

Pascal, John M., et al.. (2016). Evaluating Parp1 domains as gossypol targets. Moscow University Biological Sciences Bulletin. 71(4). 235–239. 2 indexed citations

16.

Герасимова, Н. С., et al.. (2015). Repair of chromatinized DNA. Moscow University Biological Sciences Bulletin. 70(3). 122–126. 1 indexed citations

17.

Valieva, Maria E., et al.. (2015). Структура и функции шаперона гистонов FACT. Молекулярная биология. 49(6). 891–904. 16 indexed citations

18.

Kudryashova, Kseniya S., Olga I. Kulaeva, Alexander S. Solonin, et al.. (2015). Preparation of mononucleosomal templates for analysis of transcription with RNA polymerase using spFRET. Methods in Molecular Biology. Chromatin protocols. 1288. 395–412. 7 indexed citations

19.

Walter, Wendy, et al.. (2003). Assay of the Fate of the Nucleosome During Transcription by RNA Polymerase II. Methods in enzymology on CD-ROM/Methods in enzymology. 371. 564–577. 14 indexed citations

20.

Бондаренко, В. А., et al.. (2003). Assay of Prokaryotic Enhancer Activity over a Distance In Vitro. Methods in enzymology on CD-ROM/Methods in enzymology. 370. 324–337. 5 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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