Scott R. Burrows

13.5k total citations · 2 hit papers
172 papers, 10.7k citations indexed

About

Scott R. Burrows is a scholar working on Immunology, Oncology and Epidemiology. According to data from OpenAlex, Scott R. Burrows has authored 172 papers receiving a total of 10.7k indexed citations (citations by other indexed papers that have themselves been cited), including 117 papers in Immunology, 88 papers in Oncology and 45 papers in Epidemiology. Recurrent topics in Scott R. Burrows's work include Immune Cell Function and Interaction (93 papers), Viral-associated cancers and disorders (74 papers) and T-cell and B-cell Immunology (64 papers). Scott R. Burrows is often cited by papers focused on Immune Cell Function and Interaction (93 papers), Viral-associated cancers and disorders (74 papers) and T-cell and B-cell Immunology (64 papers). Scott R. Burrows collaborates with scholars based in Australia, United Kingdom and United States. Scott R. Burrows's co-authors include Rajiv Khanna, Denis J. Moss, James McCluskey, Jamie Rossjohn, John J. Miles, I S Misko, Jacqueline M. Burrows, Anthony W. Purcell, Lars Kjer‐Nielsen and Sharon L. Silins and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Scott R. Burrows

171 papers receiving 10.5k citations

Hit Papers

align trajectories

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.

Immune self-reactivity triggered by drug-modified HLA-peptide repertoire

2012 513 citations J.P. Vivian, Zhenjun Chen et al. profile →
Estimating the global burden of Epstein–Barr virus-related cancers

2021 163 citations Yide Wong, Michael T. Meehan et al. Journal of Cancer Research and Clinical Oncology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Scott R. Burrows Australia	62	7.1k	4.6k	2.8k	1.8k	1.7k	172	10.7k
Denis J. Moss Australia	55	4.8k 0.7×	5.6k 1.2×	2.9k 1.1×	2.0k 1.1×	1.1k 0.7×	141	8.9k
Maria G. Masucci Sweden	56	4.1k 0.6×	5.9k 1.3×	2.9k 1.0×	1.9k 1.1×	4.1k 2.5×	228	11.0k
David A. Thorley‐Lawson United States	59	3.6k 0.5×	8.1k 1.8×	3.6k 1.3×	3.7k 2.0×	2.4k 1.4×	115	12.2k
Harlan Robins United States	55	5.6k 0.8×	4.7k 1.0×	1.2k 0.4×	897 0.5×	3.1k 1.8×	128	10.5k
Michael Stürzl Germany	53	2.0k 0.3×	3.9k 0.8×	1.8k 0.7×	1.0k 0.6×	2.4k 1.4×	194	7.7k
David M. Tarlinton Australia	68	12.3k 1.7×	2.5k 0.5×	1.1k 0.4×	730 0.4×	4.8k 2.9×	183	17.0k
Riccardo Dolcetti Italy	48	2.1k 0.3×	4.8k 1.0×	1.4k 0.5×	3.2k 1.8×	1.6k 0.9×	255	8.3k
Esteban Celis United States	63	13.5k 1.9×	8.6k 1.9×	2.1k 0.8×	529 0.3×	5.4k 3.2×	205	18.7k
Anne Durandy France	56	7.0k 1.0×	1.9k 0.4×	2.0k 0.7×	585 0.3×	3.4k 2.0×	196	11.5k
Carola G. Vinuesa Australia	54	11.2k 1.6×	1.7k 0.4×	992 0.4×	761 0.4×	2.9k 1.7×	117	14.8k

Countries citing papers authored by Scott R. Burrows

Since Specialization

Citations

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

Fields of papers citing papers by Scott R. Burrows

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott R. Burrows. 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 Scott R. Burrows. The network helps show where Scott R. Burrows may publish in the future.

Co-authorship network of co-authors of Scott R. Burrows

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Wong, Yide, Michael T. Meehan, Scott R. Burrows, Denise L. Doolan, & John J. Miles. (2021). Estimating the global burden of Epstein–Barr virus-related cancers. Journal of Cancer Research and Clinical Oncology. 148(1). 31–46. 163 indexed citations breakdown →

2.

Pender, Michael P., Peter A. Csurhes, Jacqueline M. Burrows, & Scott R. Burrows. (2017). Defective T‐cell control of Epstein–Barr virus infection in multiple sclerosis. Clinical & Translational Immunology. 6(1). 100 indexed citations

3.

Pender, Michael P., Peter A. Csurhes, & Scott R. Burrows. (2015). Impaired T cell control of Epstein-Barr virus infection in multiple sclerosis. Multiple Sclerosis Journal. 21(14). 1 indexed citations

4.

Burrows, Scott R. & John J. Miles. (2013). Immune Parameters to Consider When Choosing T-Cell Receptors for Therapy. Frontiers in Immunology. 4. 229–229. 8 indexed citations

5.

Wooldridge, Linda, Mathew Clement, Anna Lissina, et al.. (2010). MHC Class I Molecules with Superenhanced CD8 Binding Properties Bypass the Requirement for Cognate TCR Recognition and Nonspecifically Activate CTLs. The Journal of Immunology. 184(7). 3357–3366. 29 indexed citations

6.

Beddoe, Travis, Zhenjun Chen, Craig S. Clements, et al.. (2009). Antigen Ligation Triggers a Conformational Change within the Constant Domain of the αβ T Cell Receptor. Immunity. 30(6). 777–788. 94 indexed citations

7.

Miles, John J., Natalie A. Borg, Rebekah M. Brennan, et al.. (2006). TCRα Genes Direct MHC Restriction in the Potent Human T Cell Response to a Class I-Bound Viral Epitope. The Journal of Immunology. 177(10). 6804–6814. 57 indexed citations

8.

Miles, John J., Natalie A. Borg, Sharon L. Silins, et al.. (2005). CTL Recognition of a Bulged Viral Peptide Involves Biased TCR Selection. The Journal of Immunology. 175(6). 3826–3834. 83 indexed citations

9.

Ely, Lauren K., Travis Beddoe, Craig S. Clements, et al.. (2005). Antagonism of Antiviral and Allogeneic Activity of a Human Public CTL Clonotype by a Single Altered Peptide Ligand: Implications for Allograft Rejection. The Journal of Immunology. 174(9). 5593–5601. 26 indexed citations

10.

Macdonald, W.A., Anthony W. Purcell, Nicole A. Mifsud, et al.. (2003). A Naturally Selected Dimorphism within the HLA-B44 Supertype Alters Class I Structure, Peptide Repertoire, and T Cell Recognition. The Journal of Experimental Medicine. 198(5). 679–691. 167 indexed citations

11.

Burrows, Scott R., Rebecca Elkington, John J. Miles, et al.. (2003). Promiscuous CTL Recognition of Viral Epitopes on Multiple Human Leukocyte Antigens: Biological Validation of the Proposed HLA A24 Supertype. The Journal of Immunology. 171(3). 1407–1412. 38 indexed citations

12.

Purcell, Anthony W., Jeffrey J. Gorman, Marina García-Peydró, et al.. (2001). Quantitative and Qualitative Influences of Tapasin on the Class I Peptide Repertoire. The Journal of Immunology. 166(2). 1016–1027. 129 indexed citations

13.

Peh, Chen Au, Nihay Laham-Karam, Scott R. Burrows, Yong Zhu, & James McCluskey. (2000). Distinct Functions of Tapasin Revealed by Polymorphism in MHC Class I Peptide Loading. The Journal of Immunology. 164(1). 292–299. 49 indexed citations

14.

Kienzle, Norbert, Marion Buck, Sharon L. Silins, et al.. (2000). Differential Splicing of Antigen-Encoding RNA Reduces Endogenous Epitope Presentation That Regulates the Expansion and Cytotoxicity of T Cells. The Journal of Immunology. 165(4). 1840–1846. 4 indexed citations

15.

Khanna, Rajiv, Sharon L. Silins, Zhiping Weng, et al.. (1999). Cytotoxic T cell recognition of allelic variants of HLA B35 bound to an Epstein-Barr virus epitope: influence of peptide conformation and TCR-peptide interaction. European Journal of Immunology. 29(5). 1587–1597. 16 indexed citations

16.

Khanna, Rajiv, Sharon L. Silins, Zhiping Weng, et al.. (1999). Cytotoxic T cell recognition of allelic variants of HLA B35 bound to an Epstein-Barr virus epitope: influence of peptide conformation and TCR-peptide interaction. European Journal of Immunology. 29(5). 1587–1597. 2 indexed citations

17.

Khanna, Rajiv, Scott R. Burrows, John M. Nicholls, & L M Poulsen. (1998). Identification of cytotoxic T cell epitopes within Epstein-Barr virus (EBV) oncogene latent membrane protein 1 (LMP1): evidence for HLA A2 supertype-restricted immune recognition of EBV-infected cells by LMP1-specific cytotoxic T lymphocytes. European Journal of Immunology. 28(2). 451–458. 154 indexed citations

18.

Burrows, Scott R., Sharon L. Silins, Denis J. Moss, et al.. (1995). T cell receptor repertoire for a viral epitope in humans is diversified by tolerance to a background major histocompatibility complex antigen.. The Journal of Experimental Medicine. 182(6). 1703–1715. 166 indexed citations

19.

Moss, Denis J., Scott R. Burrows, Gordon Baxter, & Martin F. Lavin. (1991). T cell-T cell killing is induced by specific epitopes: evidence for an apoptotic mechanism.. The Journal of Experimental Medicine. 173(3). 681–686. 48 indexed citations

20.

Misko, I S, et al.. (1990). Lymphokine‐activated killer (lak) cells discriminate between epstein‐barr virus (ebv)‐positive burkitt's lymphoma cells. International Journal of Cancer. 46(3). 399–404. 7 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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