Mark Egerton

2.6k total citations · 1 hit paper
23 papers, 2.2k citations indexed

About

Mark Egerton is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mark Egerton has authored 23 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 12 papers in Molecular Biology and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mark Egerton's work include T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (8 papers) and Immunotherapy and Immune Responses (6 papers). Mark Egerton is often cited by papers focused on T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (8 papers) and Immunotherapy and Immune Responses (6 papers). Mark Egerton collaborates with scholars based in Australia, United States and United Kingdom. Mark Egerton's co-authors include Roland Scollay, Ken Shortman, Stanley Falkow, Gwyneth Bertram, Brendan P. Cormack, Neil A. R. Gow, Alistair J. P. Brown, Gerald J. Spangrude, Li Wu and Susan Raths and has published in prestigious journals such as Nature, Biochemical Journal and Biochemical and Biophysical Research Communications.

In The Last Decade

Mark Egerton

23 papers receiving 2.1k citations

Hit Papers

Yeast-enhanced green fluorescent protein (yEGFP): a repor... 1997 2026 2006 2016 1997 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Egerton Australia 19 1.3k 732 428 323 174 23 2.2k
Dorothy Hudig United States 28 1.1k 0.8× 1.1k 1.5× 518 1.2× 211 0.7× 100 0.6× 79 2.4k
Catherine R. Ferenz United States 11 1.2k 1.0× 937 1.3× 419 1.0× 183 0.6× 74 0.4× 11 2.3k
Daniel C. Hoessli Switzerland 26 1.6k 1.2× 885 1.2× 264 0.6× 597 1.8× 126 0.7× 92 2.7k
Barbara Wolff Austria 18 2.5k 1.9× 521 0.7× 442 1.0× 293 0.9× 170 1.0× 30 3.3k
Shi‐Hsiang Shen Canada 27 2.0k 1.6× 665 0.9× 363 0.8× 202 0.6× 163 0.9× 46 2.7k
Hanne L. Ostergaard Canada 26 1.1k 0.9× 1.2k 1.6× 343 0.8× 250 0.8× 43 0.2× 49 2.3k
Lisa Rothstein United States 16 2.1k 1.6× 1.4k 1.9× 615 1.4× 531 1.6× 69 0.4× 20 3.3k
Kerry Kelleher United States 18 831 0.6× 484 0.7× 321 0.8× 209 0.6× 45 0.3× 26 1.8k
Patricia M. Cameron United States 26 1.3k 1.0× 1.2k 1.7× 535 1.3× 127 0.4× 53 0.3× 36 2.8k
Jon R. Wiener United States 21 981 0.8× 351 0.5× 336 0.8× 168 0.5× 289 1.7× 33 1.7k

Countries citing papers authored by Mark Egerton

Since Specialization
Citations

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

Fields of papers citing papers by Mark Egerton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Egerton

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Egerton. A scholar is included among the top collaborators of Mark Egerton 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 Mark Egerton. Mark Egerton 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.
Furness, L. Mike, et al.. (2000). Expression databases - resources for pharmacogenomic R&D. Pharmacogenomics. 1(3). 281–288. 3 indexed citations
2.
Weston, Simon A., Roger Camble, Ian W. Taylor, et al.. (1998). Crystal structure of the anti-fungal target N-myristoyl transferase. Nature Structural Biology. 5(3). 213–221. 93 indexed citations
3.
Silins, Ginters, Sean M. Grimmond, Mark Egerton, & Nicholas K. Hayward. (1997). Analysis of the Promoter Region of the Human VEGF-Related Factor Gene. Biochemical and Biophysical Research Communications. 230(2). 413–418. 41 indexed citations
4.
Shafman, Timothy D., Padmini S. Kedar, Kevin J. Spring, et al.. (1997). Interaction between ATM protein and c-Abl in response to DNA damage. Nature. 387(6632). 520–523. 381 indexed citations
5.
Ntwasa, Monde, Mark Egerton, & Nicholas J. Gay. (1997). Sequence and expression of Drosophila myristoyl-CoA:protein N-myristoyl transferase: evidence for proteolytic processing and membrane localisation. Journal of Cell Science. 110(2). 149–156. 29 indexed citations
6.
Egerton, Mark, David Fitzpatrick, Andrew D. Catling, & Anne Kelso. (1996). Differential activation of T cell cytokine production by the extracellular signal‐regulated kinase (ERK) signaling pathway. European Journal of Immunology. 26(10). 2279–2285. 49 indexed citations
8.
9.
Quelle, Frederick W., Mark Egerton, Lawrence E. Samelson, & Don M. Wojchowski. (1992). Cytokine-induced phosphorylation of pp100 in FDC-ER cells is at tyrosine residues. Biochemical and Biophysical Research Communications. 188(3). 1040–1046. 2 indexed citations
10.
Sarosi, George A., Pamela M. Thomas, Mark Egerton, et al.. (1992). Characterization of the T cell antigen receptor - p60fyn protein tyrosine kinase association by chemical cross-linking. International Immunology. 4(11). 1211–1217. 42 indexed citations
11.
Samelson, Lawrence E., Mark Egerton, Pamela M. Thomas, & Ronald L. Wange. (1992). The T Cell Antigen Receptor Tyrosine Kinase Pathway. Advances in experimental medicine and biology. 323. 9–16. 4 indexed citations
12.
Dulić, Vjekoslav, et al.. (1991). [48] Yeast endocytosis assays. Methods in enzymology on CD-ROM/Methods in enzymology. 194. 697–710. 188 indexed citations
13.
Wu, Li, et al.. (1991). CD4 expressed on earliest T-lineage precursor cells in the adult murine thymus. Nature. 349(6304). 71–74. 286 indexed citations
14.
Wu, Li, et al.. (1990). CD4CD8 thymocytes that express the T cell receptor may have previously expressed CD8. International Immunology. 2(1). 51–56. 39 indexed citations
15.
Egerton, Mark & Roland Scollay. (1990). Intrathymic selection of murine TCRαβ+CD4CD8 thymocytes. International Immunology. 2(2). 157–163. 48 indexed citations
16.
Egerton, Mark, et al.. (1990). Cell generation within human thymic subsets defined by selective expression of CD45 (T200) isoforms. Human Immunology. 27(4). 333–347. 20 indexed citations
17.
Egerton, Mark, Ken Shortman, & Roland Scollay. (1990). The kinetics of immature murine thymocyte development in vivo. International Immunology. 2(6). 501–507. 63 indexed citations
18.
Egerton, Mark, et al.. (1988). Subpopulations of CD4-CD8-murine thymocytes: differences in proliferation rate in vivo and proliferative responses in vitro. European Journal of Immunology. 18(2). 261–268. 30 indexed citations
19.
Shortman, Ken, Anne Wilson, Mark Egerton, Martin J. Pearse, & Roland Scollay. (1988). Immature CD4− CD8+ murine thymocytes. Cellular Immunology. 113(2). 462–479. 88 indexed citations
20.
Scollay, Roland, Anne E. Wilson, Angela D’Amico, et al.. (1988). Developmental Status and Reconstitution Potential of Subpopulations of Murine Thymocytes. Immunological Reviews. 104(1). 81–120. 191 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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