Jens Derbinski

2.9k total citations · 1 hit paper
18 papers, 2.3k citations indexed

About

Jens Derbinski is a scholar working on Immunology, Genetics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Jens Derbinski has authored 18 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 7 papers in Genetics and 2 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Jens Derbinski's work include T-cell and B-cell Immunology (15 papers), Immune Cell Function and Interaction (12 papers) and Diabetes and associated disorders (7 papers). Jens Derbinski is often cited by papers focused on T-cell and B-cell Immunology (15 papers), Immune Cell Function and Interaction (12 papers) and Diabetes and associated disorders (7 papers). Jens Derbinski collaborates with scholars based in Germany, United States and France. Jens Derbinski's co-authors include Bruno Kyewski, Ludger Klein, Antje Schulte, Benedikt Brors, Leena Peltonen, Jörn Walter, Manfred Hergenhahn, Sascha Tierling, Maureen A. McGargill and Kristin A. Hogquist and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Nature reviews. Immunology.

In The Last Decade

Jens Derbinski

18 papers receiving 2.3k citations

Hit Papers

Promiscuous gene expression in medullary thymic epithelia... 2001 2026 2009 2017 2001 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
Jens Derbinski Germany 14 1.8k 633 516 292 263 18 2.3k
Emily S. Venanzi United States 9 1.9k 1.1× 895 1.4× 758 1.5× 358 1.2× 249 0.9× 10 2.7k
Sonia M. Parnell United Kingdom 29 1.6k 0.9× 429 0.7× 259 0.5× 576 2.0× 512 1.9× 50 2.5k
Maarit Heino Finland 12 893 0.5× 1.3k 2.0× 960 1.9× 377 1.3× 84 0.3× 13 2.2k
R. Finke Germany 21 424 0.2× 828 1.3× 647 1.3× 289 1.0× 110 0.4× 36 1.6k
Kellsey Johannes United States 13 815 0.5× 437 0.7× 306 0.6× 95 0.3× 162 0.6× 19 1.2k
Nina Horelli‐Kuitunen Finland 18 509 0.3× 561 0.9× 635 1.2× 720 2.5× 126 0.5× 37 1.9k
Magali Irla France 22 882 0.5× 152 0.2× 152 0.3× 357 1.2× 211 0.8× 46 1.4k
Maureen M. Sanz United States 13 841 0.5× 151 0.2× 728 1.4× 729 2.5× 163 0.6× 18 1.9k
Yin Luo Italy 17 645 0.4× 641 1.0× 629 1.2× 946 3.2× 564 2.1× 33 2.9k
Mark Malin Australia 11 766 0.4× 157 0.2× 122 0.2× 373 1.3× 298 1.1× 13 1.4k

Countries citing papers authored by Jens Derbinski

Since Specialization
Citations

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

Fields of papers citing papers by Jens Derbinski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jens Derbinski

This figure shows the co-authorship network connecting the top 25 collaborators of Jens Derbinski. A scholar is included among the top collaborators of Jens Derbinski 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 Jens Derbinski. Jens Derbinski 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.
Derbinski, Jens, Antje Schulte, Bruno Kyewski, & Ludger Klein. (2016). Pillars Article: Promiscuous Gene Expression in Medullary Thymic Epithelial Cells Mirrors the Peripheral Self. Nat. Immunol. 2001. 2: 1032–1039. The Journal of Immunology. 196(7). 2915–2922. 7 indexed citations
2.
Das, Anibh M., Vassili Valayannopoulos, Eva Thimm, et al.. (2016). Clinical course of 63 patients with neonatal onset urea cycle disorders in the years 2001–2013. Orphanet Journal of Rare Diseases. 11(1). 116–116. 35 indexed citations
3.
Lucca, Liliana E., Pierre‐Paul Axisa, Meryem Aloulou, et al.. (2016). Myelin oligodendrocyte glycoprotein induces incomplete tolerance of CD4+T cells specific for both a myelin and a neuronal self‐antigen in mice. European Journal of Immunology. 46(9). 2247–2259. 13 indexed citations
4.
Rattay, Kristin, Jens Derbinski, Thomas G. Hofmann, & Bruno Kyewski. (2015). Genome-wide gene expression profiling of homeodomain-interacting protein kinase 2 deficient medullary thymic epithelial cells. Genomics Data. 6. 48–50. 1 indexed citations
5.
Opladen, Thomas, Martin Lindner, Anibh M. Das, et al.. (2015). In vivo monitoring of urea cycle activity with 13C-acetate as a tracer of ureagenesis. Molecular Genetics and Metabolism. 117(1). 19–26. 3 indexed citations
7.
Oliveira, Cláudia C., Bianca Querido, Marjolein Sluijter, et al.. (2011). Peptide transporter TAP mediates between competing antigen sources generating distinct surface MHC class I peptide repertoires. European Journal of Immunology. 41(11). 3114–3124. 30 indexed citations
8.
Derbinski, Jens & Bruno Kyewski. (2010). How thymic antigen presenting cells sample the body's self-antigens. Current Opinion in Immunology. 22(5). 592–600. 71 indexed citations
9.
Tykocinski, Lars‐Oliver, Yanina Weiland, David Baddeley, et al.. (2010). Epigenetic regulation of promiscuous gene expression in thymic medullary epithelial cells. Proceedings of the National Academy of Sciences. 107(45). 19426–19431. 43 indexed citations
10.
Derbinski, Jens, et al.. (2008). Promiscuous gene expression patterns in single medullary thymic epithelial cells argue for a stochastic mechanism. Proceedings of the National Academy of Sciences. 105(2). 657–662. 155 indexed citations
11.
Cabarrocas, Julie, Cécile Cassan, Fay Magnusson, et al.. (2006). Foxp3 + CD25 + regulatory T cells specific for a neo-self-antigen develop at the double-positive thymic stage. Proceedings of the National Academy of Sciences. 103(22). 8453–8458. 81 indexed citations
12.
Derbinski, Jens & Bruno Kyewski. (2005). Linking signalling pathways, thymic stroma integrity and autoimmunity. Trends in Immunology. 26(10). 503–506. 49 indexed citations
13.
Derbinski, Jens, Benedikt Brors, Sascha Tierling, et al.. (2005). Promiscuous gene expression in thymic epithelial cells is regulated at multiple levels. The Journal of Experimental Medicine. 202(1). 33–45. 418 indexed citations
14.
Kyewski, Bruno & Jens Derbinski. (2004). Self-representation in the thymus: an extended view. Nature reviews. Immunology. 4(9). 688–698. 245 indexed citations
15.
Kyewski, Bruno, et al.. (2002). Promiscuous gene expression and central T-cell tolerance: more than meets the eye. Trends in Immunology. 23(7). 364–371. 161 indexed citations
16.
Kyewski, Bruno, Jens Derbinski, Antje Schulte, & Ludger Klein. (2002). Response to 'Lymphoid organs contain diverse cells expressing self-molecules'. Nature Immunology. 3(4). 336–336. 2 indexed citations
17.
Derbinski, Jens, Antje Schulte, Bruno Kyewski, & Ludger Klein. (2001). Promiscuous gene expression in medullary thymic epithelial cells mirrors the peripheral self. Nature Immunology. 2(11). 1032–1039. 835 indexed citations breakdown →
18.
McGargill, Maureen A., Jens Derbinski, & Kristin A. Hogquist. (2000). Receptor editing in developing T cells. Nature Immunology. 1(4). 336–341. 117 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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