Andrew Trimby

652 total citations
9 papers, 391 citations indexed

About

Andrew Trimby is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Andrew Trimby has authored 9 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 4 papers in Molecular Biology and 2 papers in Oncology. Recurrent topics in Andrew Trimby's work include Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (3 papers) and T-cell and B-cell Immunology (3 papers). Andrew Trimby is often cited by papers focused on Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (3 papers) and T-cell and B-cell Immunology (3 papers). Andrew Trimby collaborates with scholars based in United Kingdom, Australia and Denmark. Andrew Trimby's co-authors include David K. Cole, Andrew K. Sewell, Garry Dolton, Mark Peakman, Anthony K. Campbell, John J. Miles, P.J. Rizkallah, Christopher Holland, Andrew Godkin and J. P. Waud and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and The Journal of Immunology.

In The Last Decade

Andrew Trimby

9 papers receiving 387 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew Trimby United Kingdom	9	251	165	99	60	51	9	391
Andrea L Szymczak United States	4	113 0.5×	171 1.0×	59 0.6×	83 1.4×	22 0.4×	5	304
Sebastián Cruz-Gómez United States	9	151 0.6×	122 0.7×	74 0.7×	26 0.4×	18 0.4×	16	340
Anna Bulek United Kingdom	14	527 2.1×	168 1.0×	216 2.2×	90 1.5×	128 2.5×	17	652
Hiromi Motegi Japan	10	222 0.9×	572 3.5×	55 0.6×	85 1.4×	11 0.2×	16	742
Enric Gutiérrez-Martínez United Kingdom	9	185 0.7×	153 0.9×	51 0.5×	31 0.5×	15 0.3×	10	340
R. Andres Parra Sperberg United States	7	139 0.6×	160 1.0×	127 1.3×	14 0.2×	33 0.6×	9	316
Linette J. Edison United States	8	319 1.3×	128 0.8×	63 0.6×	16 0.3×	122 2.4×	12	451
William D. Chronister United States	8	187 0.7×	238 1.4×	73 0.7×	40 0.7×	79 1.5×	10	361
Bee-Cheng Sim United States	11	364 1.5×	165 1.0×	106 1.1×	27 0.5×	111 2.2×	14	573
Rachel E. Woolley United Kingdom	5	155 0.6×	194 1.2×	53 0.5×	58 1.0×	18 0.4×	6	374

Countries citing papers authored by Andrew Trimby

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Trimby

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Trimby

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Trimby. A scholar is included among the top collaborators of Andrew Trimby 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 Andrew Trimby. Andrew Trimby 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

Madura, Florian, P.J. Rizkallah, Mateusz Legut, et al.. (2019). TCR‐induced alteration of primary MHC peptide anchor residue. European Journal of Immunology. 49(7). 1052–1066. 17 indexed citations

Rius, Cristina, Alexander Greenshields‐Watson, Angharad Lloyd, et al.. (2016). T-cell libraries allow simple parallel generation of multiple peptide-specific human T-cell clones. Journal of Immunological Methods. 430. 43–50. 20 indexed citations

Cole, David K., Anna Bulek, Garry Dolton, et al.. (2016). Hotspot autoimmune T cell receptor binding underlies pathogen and insulin peptide cross-reactivity. Journal of Clinical Investigation. 126(6). 2191–2204. 113 indexed citations

Motozono, Chihiro, James A. Pearson, Evy De Leenheer, et al.. (2015). Distortion of the Major Histocompatibility Complex Class I Binding Groove to Accommodate an Insulin-derived 10-Mer Peptide. Journal of Biological Chemistry. 290(31). 18924–18933. 24 indexed citations

Dolton, Garry, Katie Tungatt, Angharad Lloyd, et al.. (2015). More tricks with tetramers: a practical guide to staining T cells with peptide–MHC multimers. Immunology. 146(1). 11–22. 90 indexed citations

Tungatt, Katie, Valentina Bianchi, Michael D. Crowther, et al.. (2014). Antibody Stabilization of Peptide–MHC Multimers Reveals Functional T Cells Bearing Extremely Low-Affinity TCRs. The Journal of Immunology. 194(1). 463–474. 45 indexed citations

Waud, J. P., Alexandra Bermúdez-Fajardo, Andrew Trimby, et al.. (2001). Measurement of proteases using chemiluminescence-resonance-energy-transfer chimaeras between green fluorescent protein and aequorin. Biochemical Journal. 357(3). 687–687. 38 indexed citations

Waud, J. P., et al.. (2001). Measurement of proteases using chemiluminescence-resonance-energy-transfer chimaeras between green fluorescent protein and aequorin. Biochemical Journal. 357(3). 687–697. 24 indexed citations

Taylor, KM, Andrew Trimby, & Anthony K. Campbell. (1997). Mutation of recombinant complement component C9 reveals the significance of the N‐terminal region for polymerization. Immunology. 91(1). 20–27. 20 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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