Jan Zrimec

1.2k total citations · 1 hit paper
27 papers, 681 citations indexed

About

Jan Zrimec is a scholar working on Molecular Biology, Ecology and Biomedical Engineering. According to data from OpenAlex, Jan Zrimec has authored 27 papers receiving a total of 681 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 4 papers in Ecology and 4 papers in Biomedical Engineering. Recurrent topics in Jan Zrimec's work include Microbial Metabolic Engineering and Bioproduction (4 papers), RNA and protein synthesis mechanisms (4 papers) and Genomics and Chromatin Dynamics (4 papers). Jan Zrimec is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (4 papers), RNA and protein synthesis mechanisms (4 papers) and Genomics and Chromatin Dynamics (4 papers). Jan Zrimec collaborates with scholars based in Sweden, Slovenia and Denmark. Jan Zrimec's co-authors include Aleksej Zelezniak, Jens Nielsen, Filip Buric, Vykintas Jauniškis, Aleš Lapanje, Sandra Viknander, Martin K. M. Engqvist, Francisco Zorrilla, Sara Jonasson and Verena Siewers and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLANT PHYSIOLOGY.

In The Last Decade

Jan Zrimec

27 papers receiving 667 citations

Hit Papers

Expanding functional protein sequence spaces using genera... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Zrimec Sweden 11 488 101 87 65 55 27 681
Gargi Bhattacharjee India 14 341 0.7× 110 1.1× 79 0.9× 42 0.6× 31 0.6× 36 667
Johannes Hemmerich Germany 14 535 1.1× 249 2.5× 126 1.4× 69 1.1× 21 0.4× 27 704
Nisarg Gohil India 14 364 0.7× 98 1.0× 14 0.2× 45 0.7× 14 0.3× 39 661
Chong Feng China 11 412 0.8× 53 0.5× 54 0.6× 42 0.6× 14 0.3× 15 606
Ruben Heck Netherlands 10 380 0.8× 135 1.3× 38 0.4× 89 1.4× 28 0.5× 11 499
Xuanming Liu China 16 435 0.9× 181 1.8× 22 0.3× 52 0.8× 77 1.4× 61 914
Sa Yang China 13 124 0.3× 38 0.4× 77 0.9× 160 2.5× 102 1.9× 49 549
Keiran Stevenson United Kingdom 3 197 0.4× 70 0.7× 26 0.3× 75 1.2× 16 0.3× 3 379
Sung Sun Yim South Korea 20 1.1k 2.2× 334 3.3× 25 0.3× 177 2.7× 53 1.0× 35 1.3k
Myung Hyun Noh South Korea 14 554 1.1× 251 2.5× 20 0.2× 75 1.2× 29 0.5× 27 644

Countries citing papers authored by Jan Zrimec

Since Specialization
Citations

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

Fields of papers citing papers by Jan Zrimec

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Zrimec

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Zrimec. A scholar is included among the top collaborators of Jan Zrimec 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 Jan Zrimec. Jan Zrimec 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.
Zrimec, Jan, Marko Petek, Katja Stare, et al.. (2025). Evaluating plant growth–defense trade-offs by modeling the interaction between primary and secondary metabolism. Proceedings of the National Academy of Sciences. 122(32). e2502160122–e2502160122. 1 indexed citations
2.
Buric, Filip, Sandra Viknander, Xiaozhi Fu, et al.. (2024). Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost. Protein Science. 34(1). e5239–e5239. 1 indexed citations
3.
Buric, Filip, Sandra Viknander, Xiaozhi Fu, et al.. (2023). The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
4.
Zrimec, Jan, Aleksej Zelezniak, & Kristina Gruden. (2022). Toward learning the principles of plant gene regulation. Trends in Plant Science. 27(12). 1206–1208. 6 indexed citations
5.
Li, Gang, Filip Buric, Jan Zrimec, et al.. (2022). Learning deep representations of enzyme thermal adaptation. Protein Science. 31(12). e4480–e4480. 20 indexed citations
6.
Petek, Marko, Tjaša Lukan, Katja Stare, et al.. (2022). A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors. PLANT PHYSIOLOGY. 191(3). 1934–1952. 7 indexed citations
7.
Zrimec, Jan & Aleksej Zelezniak. (2022). Controlling gene expression with deep generative design of regulatory DNA. Zenodo (CERN European Organization for Nuclear Research). 5 indexed citations
8.
Zrimec, Jan, Xiaozhi Fu, Azam Sheikh Muhammad, et al.. (2022). Controlling gene expression with deep generative design of regulatory DNA. Nature Communications. 13(1). 5099–5099. 57 indexed citations
9.
Zrimec, Jan & Aleksej Zelezniak. (2021). Plastic-degrading potential across the global microbiome correlates with recent pollution trends. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
10.
Jauniškis, Vykintas, Elzbieta Rembeza, Jan Zrimec, et al.. (2021). Expanding functional protein sequence spaces using generative adversarial networks. Nature Machine Intelligence. 3(4). 324–333. 202 indexed citations breakdown →
11.
Li, Gang, Yating Hu, Jan Zrimec, et al.. (2021). Bayesian genome scale modelling identifies thermal determinants of yeast metabolism. Nature Communications. 12(1). 190–190. 31 indexed citations
12.
Zrimec, Jan, et al.. (2021). Plastic-Degrading Potential across the Global Microbiome Correlates with Recent Pollution Trends. mBio. 12(5). e0215521–e0215521. 83 indexed citations
13.
Zrimec, Jan, et al.. (2021). Learning the Regulatory Code of Gene Expression. Frontiers in Molecular Biosciences. 8. 673363–673363. 22 indexed citations
14.
Zrimec, Jan, Filip Buric, Azam Sheikh Muhammad, et al.. (2020). Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure. Nature Communications. 11(1). 6141–6141. 111 indexed citations
15.
Zrimec, Jan. (2020). Multiple plasmid origin‐of‐transfer regions might aid the spread of antimicrobial resistance to human pathogens. MicrobiologyOpen. 9(12). e1129–e1129. 7 indexed citations
16.
Buric, Filip, Jan Zrimec, & Aleksej Zelezniak. (2020). Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra. Patterns. 1(9). 100137–100137. 2 indexed citations
18.
Rijavec, Tomaž, Jan Zrimec, Rob J. M. van Spanning, & Aleš Lapanje. (2019). Natural Microbial Communities Can Be Manipulated by Artificially Constructed Biofilms. Advanced Science. 6(22). 1901408–1901408. 19 indexed citations
19.
Zrimec, Jan & Aleš Lapanje. (2018). DNA structure at the plasmid origin-of-transfer indicates its potential transfer range. Scientific Reports. 8(1). 1820–1820. 15 indexed citations
20.
Rijavec, Tomaž, Jan Zrimec, Manca Kovač Viršek, et al.. (2016). Development of Highly Sensitive, Automatized and Portable Whole-Cell Hg Biosensor Based on Environmentally Relevant Microorganisms. Geomicrobiology Journal. 34(7). 596–605. 11 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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