Victor Sourjik

12.6k total citations · 3 hit papers
144 papers, 9.2k citations indexed

About

Victor Sourjik is a scholar working on Molecular Biology, Genetics and Biomedical Engineering. According to data from OpenAlex, Victor Sourjik has authored 144 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Molecular Biology, 79 papers in Genetics and 24 papers in Biomedical Engineering. Recurrent topics in Victor Sourjik's work include Bacterial Genetics and Biotechnology (67 papers), Gene Regulatory Network Analysis (28 papers) and Protein Structure and Dynamics (22 papers). Victor Sourjik is often cited by papers focused on Bacterial Genetics and Biotechnology (67 papers), Gene Regulatory Network Analysis (28 papers) and Protein Structure and Dynamics (22 papers). Victor Sourjik collaborates with scholars based in Germany, United States and Switzerland. Victor Sourjik's co-authors include Howard C. Berg, Ned S. Wingreen, Rémy Colin, Leanid Laganenka, David Kentner, Rüdiger Schmitt, Silke Neumann, Shuangyu Bi, Nikita Vladimirov and Bin Ni and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Victor Sourjik

138 papers receiving 9.0k citations

Hit Papers

Soft erythrocyte-based ba... 2018 2026 2020 2023 2018 2021 2021 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Victor Sourjik Germany 52 6.2k 3.2k 1.7k 1.2k 1.1k 144 9.2k
Judith P. Armitage United Kingdom 52 5.8k 0.9× 2.9k 0.9× 1.2k 0.7× 1.5k 1.2× 1.2k 1.0× 175 8.7k
Michio Homma Japan 53 5.3k 0.9× 3.2k 1.0× 1.1k 0.7× 1.3k 1.1× 1.4k 1.3× 291 8.6k
Keiichi Namba Japan 62 7.8k 1.3× 5.2k 1.6× 968 0.6× 2.9k 2.4× 1.0k 0.9× 326 13.2k
John S. Parkinson United States 51 7.7k 1.3× 5.4k 1.7× 640 0.4× 1.7k 1.4× 456 0.4× 126 10.1k
David F. Blair United States 47 4.4k 0.7× 2.6k 0.8× 812 0.5× 906 0.8× 1000 0.9× 75 6.2k
Julius Adler United States 57 8.0k 1.3× 3.4k 1.0× 2.1k 1.2× 1.4k 1.1× 1.1k 1.0× 118 12.2k
Tohru Minamino Japan 55 5.0k 0.8× 5.0k 1.5× 542 0.3× 2.0k 1.7× 663 0.6× 186 8.4k
Igor B. Zhulin United States 46 5.8k 0.9× 2.7k 0.8× 706 0.4× 1.4k 1.2× 239 0.2× 122 8.8k
Robert M. Macnab United States 67 7.6k 1.2× 6.6k 2.0× 1.3k 0.8× 2.9k 2.4× 1.5k 1.3× 127 12.5k
Mark Goulian United States 44 4.5k 0.7× 2.0k 0.6× 612 0.4× 783 0.7× 332 0.3× 103 6.9k

Countries citing papers authored by Victor Sourjik

Since Specialization
Citations

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

Fields of papers citing papers by Victor Sourjik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Victor Sourjik

This figure shows the co-authorship network connecting the top 25 collaborators of Victor Sourjik. A scholar is included among the top collaborators of Victor Sourjik 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 Victor Sourjik. Victor Sourjik 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.
Wang, Liyun, et al.. (2025). Swimming or sessile: the interplay between c-di-GMP signalling and flagellar motility. Current Opinion in Microbiology. 87. 102632–102632. 2 indexed citations
2.
Muñoz, Rafael R. Segura & Victor Sourjik. (2025). Collective dynamics of Escherichia coli growth under near-lethal acid stress. mBio. 16(11). e0193225–e0193225.
3.
Robinson, David G., Jon Mallatt, Wendy Ann Peer, Victor Sourjik, & Lincoln Taiz. (2024). Cell consciousness: a dissenting opinion. EMBO Reports. 25(5). 2162–2167. 4 indexed citations
4.
Mascarenhas, Judita, et al.. (2023). Engineering a Synthetic RNA Segregation System. ChemSystemsChem. 5(3). 1 indexed citations
5.
Lamprecht, Olga, et al.. (2023). Regulation by cyclic di-GMP attenuates dynamics and enhances robustness of bimodal curli gene activation in Escherichia coli. PLoS Genetics. 19(5). e1010750–e1010750. 6 indexed citations
6.
Bi, Shuangyu, et al.. (2023). Dynamic fluctuations in a bacterial metabolic network. Nature Communications. 14(1). 2173–2173. 11 indexed citations
7.
Martín‐Mora, David, Wenhao Xu, Victor Sourjik, et al.. (2022). The pH Robustness of Bacterial Sensing. mBio. 13(5). e0165022–e0165022. 9 indexed citations
8.
Skružný, Michal, et al.. (2020). The protein architecture of the endocytic coat analyzed by FRET microscopy. Molecular Systems Biology. 16(5). e9009–e9009. 15 indexed citations
9.
Malengo, Gabriele, et al.. (2020). Ratiometric population sensing by a pump-probe signaling system in Bacillus subtilis. Nature Communications. 11(1). 1176–1176. 15 indexed citations
10.
Schauer, Oliver, et al.. (2019). Red/Far‐Red Light Switchable Cargo Attachment and Release in Bacteria‐Driven Microswimmers. Advanced Healthcare Materials. 9(1). e1900956–e1900956. 38 indexed citations
11.
Colin, Rémy, Knut Drescher, & Victor Sourjik. (2019). Chemotactic behaviour of Escherichia coli at high cell density. Nature Communications. 10(1). 39 indexed citations
12.
Ni, Bin, Rémy Colin, Hannes Link, Robert G. Endres, & Victor Sourjik. (2019). Growth-rate dependent resource investment in bacterial motile behavior quantitatively follows potential benefit of chemotaxis. Proceedings of the National Academy of Sciences. 117(1). 595–601. 86 indexed citations
13.
Laganenka, Leanid & Victor Sourjik. (2017). Autoinducer 2-Dependent Escherichia coli Biofilm Formation Is Enhanced in a Dual-Species Coculture. Applied and Environmental Microbiology. 84(5). 90 indexed citations
14.
Laganenka, Leanid, Rémy Colin, & Victor Sourjik. (2016). Chemotaxis towards autoinducer 2 mediates autoaggregation in Escherichia coli. Nature Communications. 7(1). 12984–12984. 158 indexed citations
15.
Steuer, Ralf, Steffen Waldherr, Victor Sourjik, & Markus Kollmann. (2011). Robust Signal Processing in Living Cells. PLoS Computational Biology. 7(11). e1002218–e1002218. 34 indexed citations
16.
Ruttorf, Michaela, et al.. (2008). Protein exchange dynamics at chemoreceptor clusters in Escherichia coli. Proceedings of the National Academy of Sciences. 105(17). 6403–6408. 71 indexed citations
17.
Endres, Robert G., Olga Oleksiuk, Clinton H. Hansen, et al.. (2008). Variable sizes of Escherichia coli chemoreceptor signaling teams. Molecular Systems Biology. 4(1). 211–211. 61 indexed citations
18.
Plaimas, Kitiporn, Jan‐Philipp Mallm, Marcus Oswald, et al.. (2008). Machine learning based analyses on metabolic networks supports high-throughput knockout screens. BMC Systems Biology. 2(1). 67–67. 36 indexed citations
19.
Sourjik, Victor & Howard C. Berg. (2002). Binding of the Escherichia coli response regulator CheY to its target measured in vivo by fluorescence resonance energy transfer. Proceedings of the National Academy of Sciences. 99(20). 12669–12674. 218 indexed citations
20.
Sourjik, Victor & Howard C. Berg. (2001). Receptor sensitivity in bacterial chemotaxis. Proceedings of the National Academy of Sciences. 99(1). 123–127. 419 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026