Leon Eyrich Jessen

1.9k total citations
18 papers, 555 citations indexed

About

Leon Eyrich Jessen is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Leon Eyrich Jessen has authored 18 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Immunology and 3 papers in Oncology. Recurrent topics in Leon Eyrich Jessen's work include vaccines and immunoinformatics approaches (6 papers), T-cell and B-cell Immunology (5 papers) and Immunotherapy and Immune Responses (3 papers). Leon Eyrich Jessen is often cited by papers focused on vaccines and immunoinformatics approaches (6 papers), T-cell and B-cell Immunology (5 papers) and Immunotherapy and Immune Responses (3 papers). Leon Eyrich Jessen collaborates with scholars based in Denmark, United States and Argentina. Leon Eyrich Jessen's co-authors include Morten Nielsen, Alessandro Montemurro, Bjoern Peters, Amalie Kai Bentzen, William D. Chronister, Sine Reker Hadrup, Austin Crinklaw, Helle Rus Povlsen, Vanessa Jurtz and Ole Winther and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Nature Biotechnology.

In The Last Decade

Leon Eyrich Jessen

16 papers receiving 550 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leon Eyrich Jessen Denmark 11 319 318 141 123 48 18 555
Valentina Barrera United Kingdom 11 218 0.7× 99 0.3× 40 0.3× 24 0.2× 29 0.6× 20 597
Timothy M. Hanley United States 9 549 1.7× 204 0.6× 53 0.4× 48 0.4× 97 2.0× 17 852
Zenda Woodman South Africa 16 163 0.5× 205 0.6× 42 0.3× 77 0.6× 193 4.0× 26 600
Yasuo Hitsumoto Japan 12 203 0.6× 188 0.6× 59 0.4× 54 0.4× 60 1.3× 42 509
Jackeline F. Romero Switzerland 15 483 1.5× 400 1.3× 41 0.3× 91 0.7× 40 0.8× 18 900
Durga Bhavani Dandamudi United States 6 739 2.3× 190 0.6× 23 0.2× 86 0.7× 44 0.9× 8 874
Lolita Bebris United States 6 233 0.7× 183 0.6× 19 0.1× 45 0.4× 24 0.5× 8 502
Ariel H. Achtman Germany 13 323 1.0× 168 0.5× 11 0.1× 49 0.4× 33 0.7× 15 690
Peter Bergqvist Sweden 9 369 1.2× 138 0.4× 38 0.3× 69 0.6× 53 1.1× 10 504
Jacqueline Bixby United States 6 225 0.7× 308 1.0× 32 0.2× 60 0.5× 79 1.6× 9 512

Countries citing papers authored by Leon Eyrich Jessen

Since Specialization
Citations

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

Fields of papers citing papers by Leon Eyrich Jessen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leon Eyrich Jessen. 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 Leon Eyrich Jessen. The network helps show where Leon Eyrich Jessen may publish in the future.

Co-authorship network of co-authors of Leon Eyrich Jessen

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

All Works

18 of 18 papers shown
1.
Zhang, Yichang, Josué L. Castro‐Mejía, Ling Deng, et al.. (2025). The influence of early life exposures on the infant gut virome. Gut Microbes. 17(1). 2501194–2501194.
2.
Skougaard, Marie, et al.. (2025). Single-cell RNA sequencing highlights the influence of innate and adaptive immune response mechanisms in psoriatic arthritis. Frontiers in Immunology. 15. 1490051–1490051. 2 indexed citations
3.
Pyke, Charles, et al.. (2024). A systematic evaluation of state-of-the-art deconvolution methods in spatial transcriptomics: insights from cardiovascular disease and chronic kidney disease. SHILAP Revista de lepidopterología. 4. 1352594–1352594. 4 indexed citations
4.
5.
Montemurro, Alessandro, Helle Rus Povlsen, Leon Eyrich Jessen, & Morten Nielsen. (2023). Benchmarking data-driven filtering for denoising of TCRpMHC single-cell data. Scientific Reports. 13(1). 16147–16147. 10 indexed citations
6.
7.
Montemurro, Alessandro, Leon Eyrich Jessen, & Morten Nielsen. (2022). NetTCR-2.1: Lessons and guidance on how to develop models for TCR specificity predictions. Frontiers in Immunology. 13. 1055151–1055151. 30 indexed citations
8.
Sulaieva, Oksana, Leon Eyrich Jessen, Ruchi Jain, et al.. (2021). Reduced expression of OXPHOS and DNA damage genes is linked to protection from microvascular complications in long-term type 1 diabetes: the PROLONG study. Scientific Reports. 11(1). 20735–20735. 7 indexed citations
9.
Montemurro, Alessandro, Helle Rus Povlsen, Amalie Kai Bentzen, et al.. (2021). NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data. Communications Biology. 4(1). 1060–1060. 143 indexed citations
10.
Chronister, William D., Austin Crinklaw, Swapnil Mahajan, et al.. (2021). TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors. Frontiers in Immunology. 12. 640725–640725. 86 indexed citations
11.
Barra, Carolina, Chloé Ackaert, Birkir Reynisson, et al.. (2020). Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction. Frontiers in Immunology. 11. 1304–1304. 21 indexed citations
12.
Jensen, Kamilla Kjærgaard, Vasileios Rantos, Tobias Hegelund Olsen, et al.. (2019). TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexes. Scientific Reports. 9(1). 14530–14530. 43 indexed citations
13.
Deng, Ling, Josué L. Castro‐Mejía, Witold Kot, et al.. (2019). A Protocol for Extraction of Infective Viromes Suitable for Metagenomics Sequencing from Low Volume Fecal Samples. Viruses. 11(7). 667–667. 33 indexed citations
14.
Bentzen, Amalie Kai, Kamilla Kjærgaard Jensen, Andrea Marion Marquard, et al.. (2018). T cell receptor fingerprinting enables in-depth characterization of the interactions governing recognition of peptide–MHC complexes. Nature Biotechnology. 36(12). 1191–1196. 68 indexed citations
15.
Burdukiewicz, Michał, et al.. (2018). Conference Report: Why R? 2018. Insecta mundi. 10(2). 572–578.
16.
Bønnelykke, Klaus, Michael D. Evans, Jonathan Thorsen, et al.. (2017). Cadherin-related Family Member 3 Genetics and Rhinovirus C Respiratory Illnesses. American Journal of Respiratory and Critical Care Medicine. 197(5). 589–594. 63 indexed citations
17.
Jessen, Leon Eyrich, Ilka Hoof, Ole Lund, & Morten Nielsen. (2013). SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments. Nucleic Acids Research. 41(W1). W286–W291. 16 indexed citations
18.
Gnidehou, Sédami, Leon Eyrich Jessen, Stéphane Gangnard, et al.. (2010). Insight into Antigenic Diversity of VAR2CSA-DBL5ε Domain from Multiple Plasmodium falciparum Placental Isolates. PLoS ONE. 5(10). e13105–e13105. 14 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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