Boyan Bonev

5.7k total citations · 2 hit papers
21 papers, 2.9k citations indexed

About

Boyan Bonev is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Boyan Bonev has authored 21 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Genetics. Recurrent topics in Boyan Bonev's work include Genomics and Chromatin Dynamics (10 papers), Epigenetics and DNA Methylation (9 papers) and RNA Research and Splicing (9 papers). Boyan Bonev is often cited by papers focused on Genomics and Chromatin Dynamics (10 papers), Epigenetics and DNA Methylation (9 papers) and RNA Research and Splicing (9 papers). Boyan Bonev collaborates with scholars based in United Kingdom, Germany and France. Boyan Bonev's co-authors include Giacomo Cavalli, Nancy Papalopulu, Quentin Szabo, Giorgio L. Papadopoulos, Peter Stanley, Yaniv Lubling, Lauriane Fritsch, Xiaole Xu, Xiaodan Lv and Netta Mendelson Cohen and has published in prestigious journals such as Cell, Nature Genetics and Nature Neuroscience.

In The Last Decade

Boyan Bonev

21 papers receiving 2.9k citations

Hit Papers

Multiscale 3D Genome Rewiring during Mouse Neural Develop... 2016 2026 2019 2022 2017 2016 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Boyan Bonev United Kingdom 15 2.6k 637 436 427 188 21 2.9k
Rosa Castanon United States 17 2.6k 1.0× 770 1.2× 156 0.4× 431 1.0× 137 0.7× 20 3.2k
Gilad D. Evrony United States 14 1.8k 0.7× 417 0.7× 592 1.4× 946 2.2× 98 0.5× 25 2.6k
Jennifer A. Erwin United States 16 2.5k 1.0× 337 0.5× 977 2.2× 609 1.4× 94 0.5× 25 3.0k
Sol Katzman United States 30 3.0k 1.2× 537 0.8× 821 1.9× 688 1.6× 187 1.0× 63 3.7k
Xuyu Cai United States 14 1.9k 0.7× 375 0.6× 810 1.9× 942 2.2× 86 0.5× 23 2.7k
Laurence Ettwiller United States 22 2.0k 0.7× 297 0.5× 274 0.6× 479 1.1× 296 1.6× 49 2.5k
Lars Wittler Germany 24 2.5k 1.0× 313 0.5× 792 1.8× 456 1.1× 57 0.3× 46 2.9k
Kazuhiro R. Nitta Japan 13 2.8k 1.0× 302 0.5× 226 0.5× 504 1.2× 48 0.3× 30 3.1k
Peter J. Skene United States 14 2.7k 1.0× 284 0.4× 224 0.5× 757 1.8× 37 0.2× 22 3.1k
Hitoshi Miyachi Japan 25 1.9k 0.7× 347 0.5× 163 0.4× 477 1.1× 281 1.5× 65 3.0k

Countries citing papers authored by Boyan Bonev

Since Specialization
Citations

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

Fields of papers citing papers by Boyan Bonev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Boyan Bonev

This figure shows the co-authorship network connecting the top 25 collaborators of Boyan Bonev. A scholar is included among the top collaborators of Boyan Bonev 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 Boyan Bonev. Boyan Bonev 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.
Smith, Laura, Sri Rahayu Lestari, Alex Appert, et al.. (2025). CRAMP1 drives linker histone expression to enable Polycomb repression. Molecular Cell. 85(13). 2503–2516.e8. 3 indexed citations
2.
Masserdotti, Giacomo, Tatiana Simon, Tamás Schauer, et al.. (2024). Direct neuronal reprogramming of mouse astrocytes is associated with multiscale epigenome remodeling and requires Yy1. Nature Neuroscience. 27(7). 1260–1273. 14 indexed citations
3.
Carido, Madalena, Felix Graßmann, Kirsten A. Wunderlich, et al.. (2024). The glucocorticoid receptor as a master regulator of the Müller cell response to diabetic conditions in mice. Journal of Neuroinflammation. 21(1). 33–33. 8 indexed citations
4.
Noack, Florian, et al.. (2023). Joint epigenome profiling reveals cell-type-specific gene regulatory programmes in human cortical organoids. Nature Cell Biology. 25(12). 1873–1883. 8 indexed citations
5.
6.
Bonev, Boyan, et al.. (2021). Decoding the organization, dynamics, and function of the 4D genome. Developmental Cell. 56(11). 1562–1573. 10 indexed citations
7.
Szabo, Quentin, Ivana Jerković, Giorgio L. Papadopoulos, et al.. (2020). Regulation of single-cell genome organization into TADs and chromatin nanodomains. Nature Genetics. 52(11). 1151–1157. 127 indexed citations
8.
Boxer, Lisa D., William Renthal, Tess Whitwam, et al.. (2019). MeCP2 Represses the Rate of Transcriptional Initiation of Highly Methylated Long Genes. Molecular Cell. 77(2). 294–309.e9. 79 indexed citations
9.
Szabo, Quentin, Daniel Jost, Jia‐Ming Chang, et al.. (2018). TADs are 3D structural units of higher-order chromosome organization in Drosophila. Science Advances. 4(2). eaar8082–eaar8082. 190 indexed citations
10.
Bonev, Boyan, Netta Mendelson Cohen, Quentin Szabo, et al.. (2017). Multiscale 3D Genome Rewiring during Mouse Neural Development. Cell. 171(3). 557–572.e24. 821 indexed citations breakdown →
11.
Ciabrelli, Filippo, Federico Comoglio, Simon Fellous, et al.. (2017). Stable Polycomb-dependent transgenerational inheritance of chromatin states in Drosophila. Nature Genetics. 49(6). 876–886. 73 indexed citations
12.
Bonev, Boyan & Giacomo Cavalli. (2016). Organization and function of the 3D genome. Nature Reviews Genetics. 17(11). 661–678. 720 indexed citations breakdown →
13.
Loubière, Vincent, Aubin Thomas, Boyan Bonev, et al.. (2016). Coordinate redeployment of PRC1 proteins suppresses tumor formation during Drosophila development. Nature Genetics. 48(11). 1436–1442. 67 indexed citations
14.
Bonev, Boyan & Giacomo Cavalli. (2016). Erratum: Organization and function of the 3D genome. Nature Reviews Genetics. 17(12). 772–772. 100 indexed citations
15.
Bonev, Boyan, Peter Stanley, & Nancy Papalopulu. (2012). MicroRNA-9 Modulates Hes1 Ultradian Oscillations by Forming a Double-Negative Feedback Loop. Cell Reports. 2(1). 10–18. 144 indexed citations
16.
Bonev, Boyan & Nancy Papalopulu. (2012). Methods to Analyze microRNA Expression and Function During Xenopus Development. Methods in molecular biology. 917. 445–459. 3 indexed citations
17.
Lea, Robert, Boyan Bonev, Eamon Dubaissi, Peter D. Vize, & Nancy Papalopulu. (2012). Multicolor Fluorescent In Situ mRNA Hybridization (FISH) on Whole Mounts and Sections. Methods in molecular biology. 917. 431–444. 16 indexed citations
18.
Dajas‐Bailador, Federico, Boyan Bonev, Patrícia P. Garcez, et al.. (2012). microRNA-9 regulates axon extension and branching by targeting Map1b in mouse cortical neurons. Nature Neuroscience. 15(5). 697–699. 223 indexed citations
19.
Love, Nick R., Boyan Bonev, Michael J. Gilchrist, et al.. (2011). Genome-wide analysis of gene expression during Xenopus tropicalis tadpole tail regeneration. BMC Developmental Biology. 11(1). 70–70. 70 indexed citations
20.
Bonev, Boyan, Angela Oliveira Pisco, & Nancy Papalopulu. (2011). MicroRNA-9 Reveals Regional Diversity of Neural Progenitors along the Anterior-Posterior Axis. Developmental Cell. 20(1). 19–32. 130 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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