Michael N. T. Souter

616 total citations
9 papers, 253 citations indexed

About

Michael N. T. Souter is a scholar working on Immunology, Epidemiology and Pharmacology. According to data from OpenAlex, Michael N. T. Souter has authored 9 papers receiving a total of 253 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 2 papers in Epidemiology and 1 paper in Pharmacology. Recurrent topics in Michael N. T. Souter's work include Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (7 papers) and Cytomegalovirus and herpesvirus research (2 papers). Michael N. T. Souter is often cited by papers focused on Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (7 papers) and Cytomegalovirus and herpesvirus research (2 papers). Michael N. T. Souter collaborates with scholars based in Australia, United States and China. Michael N. T. Souter's co-authors include Sidonia B. G. Eckle, Daniel G. Pellicci, James McCluskey, David P. Fairlie, Dale I. Godfrey, Igor E. Konstantinov, Adam P. Uldrich, Kirstie M. Mangas, Paul J. Neeson and Hui‐Fern Koay and has published in prestigious journals such as Frontiers in Immunology, European Journal of Immunology and Journal of Leukocyte Biology.

In The Last Decade

Michael N. T. Souter

9 papers receiving 251 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael N. T. Souter Australia	7	227	51	31	16	13	9	253
Kerri G. Lal United States	6	188 0.8×	36 0.7×	34 1.1×	21 1.3×	9 0.7×	9	216
Rajesh Lamichhane New Zealand	5	220 1.0×	38 0.7×	21 0.7×	10 0.6×	13 1.0×	6	234
Kira Smith United States	4	262 1.2×	84 1.6×	45 1.5×	37 2.3×	16 1.2×	7	314
Ingrid Gayet United States	4	223 1.0×	29 0.6×	29 0.9×	26 1.6×	8 0.6×	4	285
Maria L. Sandoval-Romero Australia	4	409 1.8×	60 1.2×	64 2.1×	27 1.7×	17 1.3×	4	455
Jacinta M. Wubben Australia	5	161 0.7×	43 0.8×	29 0.9×	10 0.6×	8 0.6×	5	213
Elena Bruni Italy	7	225 1.0×	39 0.8×	85 2.7×	15 0.9×	13 1.0×	9	299
Thomas Kraemer Germany	7	160 0.7×	26 0.5×	23 0.7×	13 0.8×	7 0.5×	10	200
Andreas Hennemann Germany	5	184 0.8×	26 0.5×	23 0.7×	7 0.4×	5 0.4×	5	208
Jane Crowe United Kingdom	5	240 1.1×	81 1.6×	31 1.0×	42 2.6×	4 0.3×	5	296

Countries citing papers authored by Michael N. T. Souter

Since Specialization

Citations

This map shows the geographic impact of Michael N. T. Souter'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 Michael N. T. Souter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael N. T. Souter more than expected).

Fields of papers citing papers by Michael N. T. Souter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael N. T. Souter. 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 Michael N. T. Souter. The network helps show where Michael N. T. Souter may publish in the future.

Co-authorship network of co-authors of Michael N. T. Souter

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

All Works

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9 of 9 papers shown

Wang, Huimeng, Michael N. T. Souter, Marcela L. Moreira, et al.. (2024). MAIT cell plasticity enables functional adaptation that drives antibacterial immune protection. Science Immunology. 9(102). eadp9841–eadp9841. 10 indexed citations

Wang, Huimeng, Xin Yi Lim, Timothy Patton, et al.. (2023). Synthetic 5-amino-6-D-ribitylaminouracil paired with inflammatory stimuli facilitates MAIT cell expansion in vivo. Frontiers in Immunology. 14. 1109759–1109759. 3 indexed citations

Wang, Huimeng, Bingjie Wang, Zhe Zhao, et al.. (2022). The balance of interleukin‐12 and interleukin‐23 determines the bias of MAIT1 versus MAIT17 responses during bacterial infection. Immunology and Cell Biology. 100(7). 547–561. 9 indexed citations

Souter, Michael N. T., et al.. (2022). Human mucosal Vα7.2+CD161hi T cell distribution at physiologic state and inHelicobacter pyloriinfection. Journal of Leukocyte Biology. 112(4). 717–732. 6 indexed citations

Moreira, Marcela L., Michael N. T. Souter, Zhenjun Chen, et al.. (2020). Hypersensitivities following allergen antigen recognition by unconventional T cells. Allergy. 75(10). 2477–2490. 13 indexed citations

Souter, Michael N. T. & Sidonia B. G. Eckle. (2020). Biased MAIT TCR Usage Poised for Limited Antigen Diversity?. Frontiers in Immunology. 11. 1845–1845. 7 indexed citations

Souter, Michael N. T., Liyen Loh, Shihan Li, et al.. (2019). Characterization of Human Mucosal‐associated Invariant T (MAIT) Cells. Current Protocols in Immunology. 127(1). e90–e90. 9 indexed citations

Reinink, Peter, Michael N. T. Souter, Tan‐Yun Cheng, et al.. (2019). CD1b presents self and Borrelia burgdorferi diacylglycerols to human T cells. European Journal of Immunology. 49(5). 737–746. 11 indexed citations

Gherardin, Nicholas A., Michael N. T. Souter, Hui‐Fern Koay, et al.. (2018). Human blood MAIT cell subsets defined using MR1 tetramers. Immunology and Cell Biology. 96(5). 507–525. 185 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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