Jon Terrett

567 total citations
10 papers, 480 citations indexed

About

Jon Terrett is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Jon Terrett has authored 10 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Cell Biology. Recurrent topics in Jon Terrett's work include Glycosylation and Glycoproteins Research (3 papers), Proteoglycans and glycosaminoglycans research (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). Jon Terrett is often cited by papers focused on Glycosylation and Glycoproteins Research (3 papers), Proteoglycans and glycosaminoglycans research (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). Jon Terrett collaborates with scholars based in United Kingdom, Germany and Switzerland. Jon Terrett's co-authors include Kerry Tyson, Sonal Patel, Graham C. Fletcher, Alasdair C. Stamps, Colin Stubberfield, Martin Pagé, Julie Loader, Paul J. Adam, Paul N. Smith and Laurent Daviet and has published in prestigious journals such as Blood, Cancer Research and Biochemical and Biophysical Research Communications.

In The Last Decade

Jon Terrett

10 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jon Terrett United Kingdom 6 331 236 94 55 47 10 480
Mélanie Franco France 13 274 0.8× 191 0.8× 38 0.4× 30 0.5× 30 0.6× 23 481
Thomas Kirkegaard‐Sørensen Denmark 4 432 1.3× 143 0.6× 50 0.5× 72 1.3× 54 1.1× 4 650
Andrew Chen United States 5 203 0.6× 86 0.4× 72 0.8× 66 1.2× 98 2.1× 6 465
Naomi Yamakawa Japan 13 267 0.8× 203 0.9× 92 1.0× 77 1.4× 103 2.2× 16 563
Yoshiya Yonekubo United States 7 451 1.4× 124 0.5× 162 1.7× 60 1.1× 78 1.7× 7 589
A. A. Karavanov United States 8 466 1.4× 144 0.6× 108 1.1× 44 0.8× 58 1.2× 12 638
Larry H. Rohde United States 15 295 0.9× 144 0.6× 107 1.1× 96 1.7× 98 2.1× 18 589
Taiko Sukezane Japan 9 292 0.9× 147 0.6× 80 0.9× 26 0.5× 49 1.0× 10 420
Inmaculada Bañón‐Rodríguez Spain 11 298 0.9× 279 1.2× 112 1.2× 49 0.9× 52 1.1× 13 561
Karin H. Yohem United States 7 263 0.8× 121 0.5× 128 1.4× 47 0.9× 70 1.5× 9 448

Countries citing papers authored by Jon Terrett

Since Specialization
Citations

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

Fields of papers citing papers by Jon Terrett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jon Terrett

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

All Works

10 of 10 papers shown
1.
Li, Zejun, Minh Thu Pham, Luke Hanley, et al.. (2020). Abstract 3243: Allogeneic anti-PTK7 CAR-T cells for the treatment of solid tumors. Cancer Research. 80(16_Supplement). 3243–3243. 4 indexed citations
2.
Krupka, Christina, Felix S. Lichtenegger, Thomas Köhnke, et al.. (2017). Targeting CD157 in AML using a novel, Fc-engineered antibody construct. Oncotarget. 8(22). 35707–35717. 31 indexed citations
3.
Krupka, Christina, Anna Jansen, Jon Terrett, et al.. (2014). Targeting AML Using an Fc-Engineered BST1/CD157 Monoclonal Antibody. Blood. 124(21). 987–987. 4 indexed citations
4.
Aud, Dee, Rachel L. Dusek, Stefano Manzini, et al.. (2014). MEN1112, a Novel Humanized De-Fucosylated Monoclonal Antibody with High Affinity and Specificity for Bst1/CD157 Antigen and Enhanced CD16 Binding. Blood. 124(21). 3607–3607. 2 indexed citations
5.
Fletcher, Graham C., et al.. (2003). Self-assembly of proteins and their nucleic acids. Journal of Nanobiotechnology. 1(1). 1–1. 23 indexed citations
6.
Boyd, Robert S., Paul J. Adam, Sonal Patel, et al.. (2003). Proteomic analysis of the cell-surface membrane in chronic lymphocytic leukemia: identification of two novel proteins, BCNP1 and MIG2B. Leukemia. 17(8). 1605–1612. 56 indexed citations
7.
Fletcher, Graham C., Sonal Patel, Kerry Tyson, et al.. (2003). hAG-2 and hAG-3, human homologues of genes involved in differentiation, are associated with oestrogen receptor-positive breast tumours and interact with metastasis gene C4.4a and dystroglycan. British Journal of Cancer. 88(4). 579–585. 156 indexed citations
9.
Patel, Sonal, Paul R. Turner, Colin Stubberfield, et al.. (2001). Hyaluronidase gene profiling and role of HYAL‐1 overexpression in an orthotopic model of prostate cancer. International Journal of Cancer. 97(4). 416–424. 48 indexed citations
10.
McKenzie, Edward A., Kerry Tyson, Alasdair C. Stamps, et al.. (2000). Cloning and Expression Profiling of Hpa2, a Novel Mammalian Heparanase Family Member. Biochemical and Biophysical Research Communications. 276(3). 1170–1177. 152 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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