Maria Poptsova

1.2k total citations · 1 hit paper
41 papers, 703 citations indexed

About

Maria Poptsova is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Maria Poptsova has authored 41 papers receiving a total of 703 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 8 papers in Genetics and 5 papers in Ecology. Recurrent topics in Maria Poptsova's work include RNA and protein synthesis mechanisms (13 papers), Genomics and Phylogenetic Studies (12 papers) and Genomics and Chromatin Dynamics (7 papers). Maria Poptsova is often cited by papers focused on RNA and protein synthesis mechanisms (13 papers), Genomics and Phylogenetic Studies (12 papers) and Genomics and Chromatin Dynamics (7 papers). Maria Poptsova collaborates with scholars based in Russia, United States and Tajikistan. Maria Poptsova's co-authors include J. Peter Gogarten, Nazar Beknazarov, Alan Herbert, А. И. Федоров, Suraj Peri, Siddharth Balachandran, Hong‐Liang Bao, Ting Zhang, Shiyu Wang and Yan Xu and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Maria Poptsova

37 papers receiving 669 citations

Hit Papers

ADAR1 masks the cancer immunotherapeutic promise of ZBP1-... 2022 2026 2023 2024 2022 50 100 150 200 250
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. ADAR1 masks the cancer immunotherapeutic promise of ZBP1-driven necroptosis
    2022 262 citations Ting Zhang, Chaoran Yin et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maria Poptsova Russia 12 584 115 88 78 73 41 703
Xian Jia China 8 401 0.7× 104 0.9× 51 0.6× 51 0.7× 30 0.4× 14 576
Constance L. Fisher United States 8 433 0.7× 60 0.5× 150 1.7× 60 0.8× 44 0.6× 12 598
Zhenping Zhong United States 12 795 1.4× 71 0.6× 166 1.9× 55 0.7× 107 1.5× 14 945
Michael J. Haykinson United States 12 542 0.9× 104 0.9× 196 2.2× 38 0.5× 78 1.1× 14 707
Shuren Liao United States 14 803 1.4× 73 0.6× 240 2.7× 31 0.4× 39 0.5× 21 886
Alexandra Richter Germany 6 321 0.5× 55 0.5× 121 1.4× 68 0.9× 30 0.4× 7 545
Colin Chih‐Chien Wu United States 11 1.2k 2.1× 89 0.8× 65 0.7× 36 0.5× 33 0.5× 17 1.3k
Danielle L. Watt United States 10 1.0k 1.8× 103 0.9× 167 1.9× 71 0.9× 27 0.4× 11 1.2k
Nobuko Hamasaki‐Katagiri United States 13 432 0.7× 52 0.5× 57 0.6× 64 0.8× 38 0.5× 23 583
Chase A. Weidmann United States 13 1.2k 2.1× 72 0.6× 49 0.6× 39 0.5× 54 0.7× 23 1.3k

Countries citing papers authored by Maria Poptsova

Since Specialization
Citations

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

Fields of papers citing papers by Maria Poptsova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Poptsova

This figure shows the co-authorship network connecting the top 25 collaborators of Maria Poptsova. A scholar is included among the top collaborators of Maria Poptsova 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 Maria Poptsova. Maria Poptsova 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.
Herbert, Alan, et al.. (2025). Benchmarking DNA large language models on quadruplexes. Computational and Structural Biotechnology Journal. 27. 992–1000.
2.
Kim, Anna, et al.. (2025). Deep learning captures the effect of epistasis in multifactorial diseases. Frontiers in Medicine. 11. 1479717–1479717. 3 indexed citations
3.
Poptsova, Maria, et al.. (2025). Kolmogorov–Arnold networks for genomic tasks. Briefings in Bioinformatics. 26(2). 3 indexed citations
4.
Herbert, Alan, et al.. (2025). Zα and Zβ Localize ADAR1 to Flipons That Modulate Innate Immunity, Alternative Splicing, and Nonsynonymous RNA Editing. International Journal of Molecular Sciences. 26(6). 2422–2422. 1 indexed citations
5.
Poptsova, Maria, et al.. (2024). Data augmentation with generative models improves detection of Non-B DNA structures. Computers in Biology and Medicine. 184. 109440–109440. 1 indexed citations
6.
7.
Nikolaev, К. Yu., et al.. (2024). Machine learning models for predicting risks of MACEs for myocardial infarction patients with different VEGFR2 genotypes. Frontiers in Medicine. 11. 1452239–1452239. 2 indexed citations
8.
Herbert, Alan, et al.. (2023). Conserved microRNAs and Flipons Shape Gene Expression during Development by Altering Promoter Conformations. International Journal of Molecular Sciences. 24(5). 4884–4884. 10 indexed citations
9.
Beknazarov, Nazar & Maria Poptsova. (2023). DeepZ: A Deep Learning Approach for Z-DNA Prediction. Methods in molecular biology. 2651. 217–226. 5 indexed citations
10.
Herbert, Alan, et al.. (2023). Unsupervised domain adaptation methods for cross-species transfer of regulatory code signals. Frontiers in Big Data. 6. 1140663–1140663. 1 indexed citations
11.
Bogorodskaya, E. M., et al.. (2023). Research of Russian physicians’ opinions on tuberculosis pharmacogenetics. International Journal of Risk & Safety in Medicine. 35(1). 25–36. 1 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.
Poptsova, Maria, et al.. (2020). Understanding cancer breakpoint determinants with omics data. 7(2). 1 indexed citations
14.
Beknazarov, Nazar, Seungmin Jin, & Maria Poptsova. (2020). Deep learning approach for predicting functional Z-DNA regions using omics data. Scientific Reports. 10(1). 19134–19134. 29 indexed citations
15.
Poptsova, Maria, et al.. (2016). Conserved 3′ UTR stem-loop structure in L1 and Alu transposons in human genome: possible role in retrotransposition. BMC Genomics. 17(1). 992–992. 9 indexed citations
16.
Poptsova, Maria, Samprit Banerjee, Ömer Gökçümen, Mark A. Rubin, & Francesca Demichelis. (2013). Impact of constitutional copy number variants on biological pathway evolution. BMC Evolutionary Biology. 13(1). 19–19. 16 indexed citations
17.
Mao, Fenglou, David Williams, Olga Zhaxybayeva, et al.. (2012). Quartet decomposition server: a platform for analyzing phylogenetic trees. BMC Bioinformatics. 13(1). 123–123. 6 indexed citations
18.
Poptsova, Maria, et al.. (2011). Intermittency as a universal characteristic of the complete chromosome DNA sequences of eukaryotes: From protozoa to human genomes. Physical Review E. 84(4). 42902–42902. 4 indexed citations
19.
Poptsova, Maria. (2009). Testing Phylogenetic Methods to Identify Horizontal Gene Transfer. Methods in molecular biology. 532. 227–240. 11 indexed citations
20.
Hamel, Lutz, et al.. (2008). Unsupervised Learning in Detection of Gene Transfer. BioMed Research International. 2008(1). 472719–472719. 4 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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