Andrew K. Sewell

16.9k total citations · 1 hit paper
199 papers, 11.4k citations indexed

About

Andrew K. Sewell is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Andrew K. Sewell has authored 199 papers receiving a total of 11.4k indexed citations (citations by other indexed papers that have themselves been cited), including 158 papers in Immunology, 47 papers in Oncology and 36 papers in Molecular Biology. Recurrent topics in Andrew K. Sewell's work include Immune Cell Function and Interaction (124 papers), T-cell and B-cell Immunology (108 papers) and Immunotherapy and Immune Responses (87 papers). Andrew K. Sewell is often cited by papers focused on Immune Cell Function and Interaction (124 papers), T-cell and B-cell Immunology (108 papers) and Immunotherapy and Immune Responses (87 papers). Andrew K. Sewell collaborates with scholars based in United Kingdom, United States and Australia. Andrew K. Sewell's co-authors include David A. Price, David K. Cole, Rodney E. Phillips, Linda Wooldridge, Garry Dolton, Emma Gostick, Bruno Laugel, Philip Goulder, Bent K. Jakobsen and John J. Miles and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Andrew K. Sewell

196 papers receiving 11.2k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Positive selection of HIV-1 cytotoxic T lymphocyte escape variants during primary infection

1997 538 citations David A. Price, Philip Goulder et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew K. Sewell United Kingdom	59	7.8k	3.2k	2.9k	1.7k	1.1k	199	11.4k
Filippo Belardelli Italy	61	10.0k 1.3×	4.4k 1.4×	3.1k 1.1×	1.4k 0.8×	1.8k 1.6×	258	14.9k
François A. Lemonnier France	51	8.1k 1.0×	1.7k 0.5×	3.1k 1.1×	1.3k 0.7×	1.4k 1.3×	191	10.6k
Francis W. Ruscetti United States	55	11.0k 1.4×	2.3k 0.7×	4.6k 1.6×	1.1k 0.6×	1.0k 0.9×	144	17.0k
David H. Lynch United States	57	9.7k 1.2×	2.8k 0.9×	7.7k 2.7×	1.6k 0.9×	2.0k 1.8×	149	16.4k
Scot A. Marsters United States	42	5.4k 0.7×	2.6k 0.8×	8.2k 2.9×	764 0.5×	1.6k 1.5×	61	13.1k
Alain Townsend United Kingdom	54	9.9k 1.3×	1.5k 0.5×	4.2k 1.5×	1.1k 0.7×	3.3k 2.9×	134	14.7k
Daniel Olive France	72	13.2k 1.7×	7.1k 2.2×	3.6k 1.3×	1.1k 0.7×	1.4k 1.3×	441	19.1k
Peter Van Endert France	55	8.4k 1.1×	3.7k 1.2×	4.6k 1.6×	638 0.4×	1.9k 1.7×	171	13.6k
Anthony W. Purcell Australia	65	8.9k 1.1×	2.0k 0.6×	6.7k 2.4×	626 0.4×	1.8k 1.7×	320	16.6k
Donald E. Mosier United States	56	5.7k 0.7×	1.3k 0.4×	2.4k 0.8×	3.0k 1.8×	1.4k 1.3×	157	10.3k

Countries citing papers authored by Andrew K. Sewell

Since Specialization

Citations

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

Fields of papers citing papers by Andrew K. Sewell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew K. Sewell

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

All Works

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20 of 20 papers shown

1.

Schwartz, J.C., Colin Farrell, Graham Freimanis, et al.. (2024). A genome assembly and transcriptome atlas of the inbred Babraham pig to illuminate porcine immunogenetic variation. Immunogenetics. 76(5-6). 361–380. 1 indexed citations

2.

Clement, Mathew, James E. McLaren, Kristin Ladell, et al.. (2021). CD8 coreceptor-mediated focusing can reorder the agonist hierarchy of peptide ligands recognized via the T cell receptor. Proceedings of the National Academy of Sciences. 118(29). 8 indexed citations

3.

Martini, Veronica, Basudev Paudyal, Matthew Edmans, et al.. (2020). Simultaneous Aerosol and Intramuscular Immunization with Influenza Vaccine Induces Powerful Protective Local T Cell and Systemic Antibody Immune Responses in Pigs. The Journal of Immunology. 206(3). 652–663. 19 indexed citations

4.

Crowther, Michael D., Garry Dolton, Mateusz Legut, et al.. (2020). Genome-wide CRISPR–Cas9 screening reveals ubiquitous T cell cancer targeting via the monomorphic MHC class I-related protein MR1. Nature Immunology. 21(2). 178–185. 166 indexed citations

5.

Yeo, Lorraine, Irma Pujol‐Autonell, Ricardo Baptista, et al.. (2019). Circulating β cell-specific CD8+ T cells restricted by high-risk HLA class I molecules show antigen experience in children with and at risk of type 1 diabetes. Clinical & Experimental Immunology. 199(3). 263–277. 26 indexed citations

6.

Rius, Cristina, Meriem Attaf, Katie Tungatt, et al.. (2018). Peptide–MHC Class I Tetramers Can Fail To Detect Relevant Functional T Cell Clonotypes and Underestimate Antigen-Reactive T Cell Populations. The Journal of Immunology. 200(7). 2263–2279. 64 indexed citations

7.

Biktasova, Asel, Michael Hajek, Andrew K. Sewell, et al.. (2017). Demethylation Therapy as a Targeted Treatment for Human Papillomavirus–Associated Head and Neck Cancer. Clinical Cancer Research. 23(23). 7276–7287. 46 indexed citations

8.

Gilham, David E., John Anderson, John S. Bridgeman, et al.. (2015). Adoptive T-Cell Therapy for Cancer in the United Kingdom: A Review of Activity for the British Society of Gene and Cell Therapy Annual Meeting 2015. Human Gene Therapy. 26(5). 276–285. 15 indexed citations

9.

Madura, Florian, P.J. Rizkallah, Kim Miles, et al.. (2013). T-cell Receptor Specificity Maintained by Altered Thermodynamics. Journal of Biological Chemistry. 288(26). 18766–18775. 32 indexed citations

10.

Clement, Mathew, Kristin Ladell, Julia Makinde, et al.. (2011). Anti-CD8 Antibodies Can Trigger CD8+ T Cell Effector Function in the Absence of TCR Engagement and Improve Peptide–MHCI Tetramer Staining. The Journal of Immunology. 187(2). 654–663. 32 indexed citations

11.

Cole, David K., Emily S.J. Edwards, Katherine K. Wynn, et al.. (2010). Modification of MHC Anchor Residues Generates Heteroclitic Peptides That Alter TCR Binding and T Cell Recognition. The Journal of Immunology. 185(4). 2600–2610. 102 indexed citations

12.

Wooldridge, Linda, Anna Lissina, David K. Cole, et al.. (2009). Tricks with tetramers: how to get the most from multimeric peptide–MHC. Immunology. 126(2). 147–164. 132 indexed citations

13.

Wooldridge, Linda, Matthew Clement, Angharad E. Fenton-May, et al.. (2008). Profound Inhibition of Antigen-Specific T-Cell Effector Functions by Dasatinib. Clinical Cancer Research. 14(8). 2484–2491. 106 indexed citations

14.

Sewell, Andrew K., Bruce L. Booth, Vincenzo Cerundolo, Rodney E. Phillips, & David A. Price. (2002). Short Communication: Differential Processing of HLA A2-Restricted HIV Type 1 Cytotoxic T Lymphocyte Epitopes. Viral Immunology. 15(1). 193–196. 5 indexed citations

15.

Kelleher, Anthony D., Bruce L. Booth, Andrew K. Sewell, et al.. (2001). Effects of Retroviral Protease Inhibitors on Proteasome Function and Processing of HIV-Derived MHC Class I-Restricted Cytotoxic T Lymphocyte Epitopes. AIDS Research and Human Retroviruses. 17(11). 1063–1066. 9 indexed citations

16.

Wilson, Jamie, Graham S. Ogg, Rachel Allen, et al.. (1998). Oligoclonal Expansions of CD8+ T Cells in Chronic HIV Infection Are Antigen Specific. The Journal of Experimental Medicine. 188(4). 785–790. 135 indexed citations

17.

Lewis, Jonathan W., Andrew K. Sewell, David A. Price, & Tim Elliott. (1998). HLA-A*0201 presents TAP-dependent peptide epitopes to cytotoxic T lymphocytes in the absence of tapasin. European Journal of Immunology. 28(10). 3214–3220. 51 indexed citations

18.

Lewis, Jonathan W., Andrew K. Sewell, David A. Price, & Tim Elliott. (1998). HLA-A*0201 presents TAP-dependent peptide epitopes to cytotoxic T lymphocytes in the absence of tapasin. European Journal of Immunology. 28(10). 3214–3220. 1 indexed citations

19.

Thorvaldsen, Joanne L., Rajesh K. Mehra, Wei Yu, Andrew K. Sewell, & Dennis R. Winge. (1995). Analysis of copper‐induced metallothionein expression using autonomously replicating plasmids in Candida glabrata. Yeast. 11(15). 1501–1511. 12 indexed citations

20.

Salt, David E., David A. Thurman, A. Brian Tomsett, & Andrew K. Sewell. (1989). Copper phytochelatins of Mimulus guttatus. Proceedings of the Royal Society of London. Series B, Biological sciences. 236(1282). 79–89. 30 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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