Mai B. Margetts

1.5k total citations
19 papers, 1.1k citations indexed

About

Mai B. Margetts is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Surgery. According to data from OpenAlex, Mai B. Margetts has authored 19 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Endocrinology, Diabetes and Metabolism and 4 papers in Surgery. Recurrent topics in Mai B. Margetts's work include Metabolism, Diabetes, and Cancer (8 papers), Growth Hormone and Insulin-like Growth Factors (6 papers) and Pancreatic function and diabetes (4 papers). Mai B. Margetts is often cited by papers focused on Metabolism, Diabetes, and Cancer (8 papers), Growth Hormone and Insulin-like Growth Factors (6 papers) and Pancreatic function and diabetes (4 papers). Mai B. Margetts collaborates with scholars based in Australia, United Kingdom and United States. Mai B. Margetts's co-authors include Michael C. Lawrence, John G. Menting, Colin W. Ward, Brian J. Smith, G.K.-W. Kong, Jonathan Whittaker, Michael A. Weiss, David Pye, Robin F. Anders and Stirling Edwards and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Mai B. Margetts

18 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
Mai B. Margetts Australia 13 741 250 192 182 109 19 1.1k
Sylviane Hoos France 18 717 1.0× 81 0.3× 117 0.6× 33 0.2× 132 1.2× 33 1.2k
David W. Keizer Australia 18 591 0.8× 84 0.3× 148 0.8× 24 0.1× 158 1.4× 41 1.1k
Sari Lusa Finland 12 549 0.7× 90 0.4× 281 1.5× 271 1.5× 107 1.0× 15 1.2k
Joke Regts Netherlands 22 694 0.9× 77 0.3× 65 0.3× 117 0.6× 366 3.4× 36 1.4k
Jérôme Vicogne France 21 739 1.0× 24 0.1× 128 0.7× 79 0.4× 144 1.3× 54 1.3k
Stephen J. Headey Australia 20 579 0.8× 174 0.7× 22 0.1× 30 0.2× 52 0.5× 46 939
Werner Tegge Germany 18 912 1.2× 28 0.1× 88 0.5× 98 0.5× 168 1.5× 46 1.4k
Morten Beck Trelle Denmark 16 933 1.3× 34 0.1× 214 1.1× 26 0.1× 153 1.4× 25 1.4k
Pablo C. Echeverría Argentina 22 1.0k 1.4× 90 0.4× 69 0.4× 25 0.1× 218 2.0× 32 1.6k
Yasuo Shirakihara Japan 15 885 1.2× 40 0.2× 85 0.4× 62 0.3× 452 4.1× 20 1.5k

Countries citing papers authored by Mai B. Margetts

Since Specialization
Citations

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

Fields of papers citing papers by Mai B. Margetts

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mai B. Margetts. 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 Mai B. Margetts. The network helps show where Mai B. Margetts may publish in the future.

Co-authorship network of co-authors of Mai B. Margetts

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

All Works

19 of 19 papers shown
1.
Margetts, Mai B., Longfei Wang, Jack Godsell, et al.. (2025). A dominant-negative IFNGR1 variant reveals broad immune cell sequestering of IFN-γ. Journal of Clinical Investigation. 135(8).
2.
Yong, Michelle K., Mai B. Margetts, Erin D. Lucas, et al.. (2024). Cytomegalovirus drives Vδ1+ γδ T cell expansion and clonality in common variable immunodeficiency. Nature Communications. 15(1). 4286–4286. 7 indexed citations
3.
Chen, Qi, Haitao Hu, Juan F. Espinosa, et al.. (2022). Activation of the human insulin receptor by non-insulin-related peptides. Nature Communications. 13(1). 5695–5695. 15 indexed citations
4.
Xu, Yibin, Mai B. Margetts, Hariprasad Venugopal, et al.. (2022). How insulin-like growth factor I binds to a hybrid insulin receptor type 1 insulin-like growth factor receptor. Structure. 30(8). 1098–1108.e6. 28 indexed citations
5.
Godsell, Jack, Lauren J. Howson, Mai B. Margetts, et al.. (2022). Case Report: Cytomegalovirus Disease Is an Under-Recognized Contributor to Morbidity and Mortality in Common Variable Immunodeficiency. Frontiers in Immunology. 13. 815193–815193. 7 indexed citations
6.
Xu, Yibin, Hariprasad Venugopal, Mai B. Margetts, et al.. (2020). How IGF-II Binds to the Human Type 1 Insulin-like Growth Factor Receptor. Structure. 28(7). 786–798.e6. 40 indexed citations
7.
Xu, Yibin, G.K.-W. Kong, John G. Menting, et al.. (2018). How ligand binds to the type 1 insulin-like growth factor receptor. Nature Communications. 9(1). 821–821. 90 indexed citations
8.
Weis, Félix, John G. Menting, Mai B. Margetts, et al.. (2018). The signalling conformation of the insulin receptor ectodomain. Nature Communications. 9(1). 4420–4420. 92 indexed citations
9.
Croll, Tristan I., Brian J. Smith, Mai B. Margetts, et al.. (2016). Higher-Resolution Structure of the Human Insulin Receptor Ectodomain: Multi-Modal Inclusion of the Insert Domain. Structure. 24(3). 469–476. 93 indexed citations
10.
Margetts, Mai B., John G. Menting, Nicholas A. Smith, et al.. (2016). Insulin Mimetic Peptide Disrupts the Primary Binding Site of the Insulin Receptor. Journal of Biological Chemistry. 291(30). 15473–15481. 33 indexed citations
11.
Menting, John G., et al.. (2015). Structural Congruency of Ligand Binding to the Insulin and Insulin/Type 1 Insulin-like Growth Factor Hybrid Receptors. Structure. 23(7). 1271–1282. 45 indexed citations
12.
Menting, John G., Jonathan Whittaker, Mai B. Margetts, et al.. (2013). How insulin engages its primary binding site on the insulin receptor. Nature. 493(7431). 241–245. 293 indexed citations
13.
14.
Menting, John G., Colin W. Ward, Mai B. Margetts, & Michael C. Lawrence. (2009). A Thermodynamic Study of Ligand Binding to the First Three Domains of the Human Insulin Receptor: Relationship between the Receptor α-Chain C-Terminal Peptide and the Site 1 Insulin Mimetic Peptides. Biochemistry. 48(23). 5492–5500. 23 indexed citations
15.
Margetts, Mai B., et al.. (2002). Antibody Responses to HPV6b E Polyproteins and Production of Monoclonal Antibodies. PubMed. 21(5). 333–338. 3 indexed citations
16.
Slakeski, Nada, et al.. (2002). Characterization and expression of a novel Porphyromonas gingivalis outer membrane protein, Omp28. Oral Microbiology and Immunology. 17(3). 150–156. 8 indexed citations
17.
Ross, B C, Dianna M. Hocking, Mai B. Margetts, et al.. (2001). Identification of vaccine candidate antigens from a genomic analysis of Porphyromonas gingivalis. Vaccine. 19(30). 4135–4142. 103 indexed citations
18.
Margetts, Mai B., Ian Barr, & Elizabeth Webb. (2000). Overexpression, Purification, and Refolding of a Porphyromonas gingivalis Cysteine Protease from Escherichia coli. Protein Expression and Purification. 18(3). 262–268. 11 indexed citations
19.
Anders, Robin F., et al.. (1998). Immunisation with recombinant AMA-1 protects mice against infection with Plasmodium chabaudi. Vaccine. 16(2-3). 240–247. 179 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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