Jan Salomonsen

1.5k total citations
23 papers, 1.1k citations indexed

About

Jan Salomonsen is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Jan Salomonsen has authored 23 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Immunology, 8 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Molecular Biology. Recurrent topics in Jan Salomonsen's work include T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (14 papers) and Immunotherapy and Immune Responses (9 papers). Jan Salomonsen is often cited by papers focused on T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (14 papers) and Immunotherapy and Immune Responses (9 papers). Jan Salomonsen collaborates with scholars based in Denmark, United Kingdom and Switzerland. Jan Salomonsen's co-authors include Jim Kaufman, Karsten Skjødt, Martin F. Flajnik, Olli Vainio, David Ávila, Jansen Jacob, Denise A. Marston, Lawrence Hunt, Hans‐Joachim Wallny and Patricia Riegert and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Immunity and The Journal of Immunology.

In The Last Decade

Jan Salomonsen

23 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Salomonsen Denmark 16 823 274 202 137 117 23 1.1k
Jansen Jacob United Kingdom 6 583 0.7× 266 1.0× 165 0.8× 131 1.0× 92 0.8× 8 904
Ronald M. Goto United States 20 855 1.0× 373 1.4× 256 1.3× 274 2.0× 220 1.9× 44 1.4k
Sarah Milne United Kingdom 12 1.2k 1.5× 379 1.4× 273 1.4× 136 1.0× 107 0.9× 16 1.8k
H. Izawa Japan 16 663 0.8× 166 0.6× 178 0.9× 147 1.1× 40 0.3× 106 930
E. Egberts Netherlands 19 904 1.1× 368 1.3× 60 0.3× 116 0.8× 81 0.7× 54 1.4k
S. J. Ewald United States 16 372 0.5× 229 0.8× 180 0.9× 179 1.3× 94 0.8× 24 702
K Hála Austria 20 620 0.8× 245 0.9× 178 0.9× 410 3.0× 176 1.5× 77 1.3k
Michael J. H. Ratcliffe Canada 27 1.1k 1.3× 628 2.3× 245 1.2× 264 1.9× 167 1.4× 69 1.9k
Larry D. Bacon United States 17 400 0.5× 250 0.9× 356 1.8× 398 2.9× 130 1.1× 36 1.1k
B Wang United States 8 630 0.8× 398 1.5× 265 1.3× 45 0.3× 26 0.2× 8 1.0k

Countries citing papers authored by Jan Salomonsen

Since Specialization
Citations

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

Fields of papers citing papers by Jan Salomonsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Salomonsen

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Salomonsen. A scholar is included among the top collaborators of Jan Salomonsen 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 Salomonsen. Jan Salomonsen 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.
Jaratlerdsiri, Weerachai, Sally R. Isberg, Damien P. Higgins, et al.. (2013). Evolution of MHC class I in the Order Crocodylia. Immunogenetics. 66(1). 53–65. 12 indexed citations
2.
Skjoedt, Mikkel‐Ole, Yaseelan Palarasah, Karina Juhl Rasmussen, et al.. (2009). Two mannose-binding lectin homologues and an MBL-associated serine protease are expressed in the gut epithelia of the urochordate species Ciona intestinalis. Developmental & Comparative Immunology. 34(1). 59–68. 31 indexed citations
3.
Koch, Michael, David Ávila, Jan Salomonsen, et al.. (2007). Structures of an MHC Class I Molecule from B21 Chickens Illustrate Promiscuous Peptide Binding. Immunity. 27(6). 885–899. 147 indexed citations
4.
Nygård, Ann-Britt, et al.. (2006). Various domains of the B-cell regulatory molecule CD72 has diverged at different rates in mammals: Cloning, transcription and mapping of porcine CD72. Developmental & Comparative Immunology. 31(5). 530–538. 3 indexed citations
5.
Nygård, Ann-Britt, et al.. (2006). Cloning, characterization and mapping of porcine CD14 reveals a high conservation of mammalian CD14 structure, expression and locus organization. Developmental & Comparative Immunology. 31(7). 729–737. 9 indexed citations
6.
Wallny, Hans‐Joachim, David Ávila, Lawrence Hunt, et al.. (2006). Peptide motifs of the single dominantly expressed class I molecule explain the striking MHC-determined response to Rous sarcoma virus in chickens. Proceedings of the National Academy of Sciences. 103(5). 1434–1439. 149 indexed citations
7.
Salomonsen, Jan, Maria Rathmann Sørensen, Denise A. Marston, et al.. (2005). Two CD1 genes map to the chicken MHC, indicating that CD1 genes are ancient and likely to have been present in the primordial MHC. Proceedings of the National Academy of Sciences. 102(24). 8668–8673. 87 indexed citations
8.
9.
Salomonsen, Jan, Denise A. Marston, David Ávila, et al.. (2003). The properties of the single chicken MHC classical class II ? chain (B-LA) gene indicate an ancient origin for the DR/E-like isotype of class II molecules. Immunogenetics. 55(9). 605–614. 57 indexed citations
10.
Salomonsen, Jan, Clive A. Tregaskes, John R. Young, et al.. (2002). The chicken CD4 gene has remained conserved in evolution. Immunogenetics. 54(7). 520–525. 21 indexed citations
11.
Lamminmäki, Urpo, et al.. (1999). Cloning and Modeling of the First Nonmammalian CD4. The Journal of Immunology. 162(7). 4115–4121. 24 indexed citations
12.
Kaufman, Jim, Jansen Jacob, Brian A. Walker, et al.. (1999). Gene organisation determines evolution of function in the chicken MHC. Immunological Reviews. 167(1). 101–117. 119 indexed citations
13.
Kaufman, Jim, Jan Salomonsen, & Martin F. Flajnik. (1994). Evolutionary conservation of MHC class I and class II molecules—different yet the same. Seminars in Immunology. 6(6). 411–424. 152 indexed citations
14.
Kaufman, Jim & Jan Salomonsen. (1992). BG: we know what it is, but what does it do?. Immunology Today. 13(1). 1–3. 36 indexed citations
15.
16.
Kaufman, Jim, et al.. (1991). Variations in the cytoplasmic region account for the heterogeneity of the chicken MHC class I (B-F) molecules. Immunogenetics. 34(2). 110–20. 14 indexed citations
17.
Kaufman, Jim, Karsten Skjoedt, & Jan Salomonsen. (1990). The MHC Molecules of Nonmammalian Vertebrates. Immunological Reviews. 113(1). 83–117. 55 indexed citations
18.
Kaufman, Jim, Jan Salomonsen, & Karsten Skjødt. (1989). B-G cDNA clones have multiple small repeats and hybridize to both chicken MHC regions. Immunogenetics. 30(6). 440–451. 44 indexed citations
19.
Kaufman, Jim, et al.. (1989). 3.3 MHC proteins and genes in birds and reptiles. Developmental & Comparative Immunology. 13(4). 374–375. 2 indexed citations
20.
Salomonsen, Jan, Karsten Skjødt, Monna Crone, & Morten Simonsen. (1987). The chicken erythrocyte-specific MHC antigen. Characterization and purification of the B-G antigen by monoclonal antibodies. Immunogenetics. 25(6). 373–382. 49 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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