Gavin Screaton

43.0k total citations · 5 hit papers
128 papers, 11.8k citations indexed

About

Gavin Screaton is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health and Molecular Biology. According to data from OpenAlex, Gavin Screaton has authored 128 papers receiving a total of 11.8k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Infectious Diseases, 49 papers in Public Health, Environmental and Occupational Health and 42 papers in Molecular Biology. Recurrent topics in Gavin Screaton's work include Mosquito-borne diseases and control (48 papers), Viral Infections and Vectors (39 papers) and Malaria Research and Control (21 papers). Gavin Screaton is often cited by papers focused on Mosquito-borne diseases and control (48 papers), Viral Infections and Vectors (39 papers) and Malaria Research and Control (21 papers). Gavin Screaton collaborates with scholars based in United Kingdom, Thailand and United States. Gavin Screaton's co-authors include Juthathip Mongkolsapaya, Wanwisa Dejnirattisai, Andrew J. McMichael, Javier F. Cáceres, David G. Jackson, Adrian R. Krainer, Xiao‐Ning Xu, Prida Malasit, Thaneeya Duangchinda and Ulf Gerth and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Gavin Screaton

126 papers receiving 11.6k 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.

Genomic structure of DNA encoding the lymphocyte homing receptor CD44 reveals at least 12 alternatively spliced exons.

1992 928 citations Gavin Screaton et al. Proceedings of the National Academy of Sciences profile →
Cross-Reacting Antibodies Enhance Dengue Virus Infection in Humans

2010 698 citations Wanwisa Dejnirattisai, Thaneeya Duangchinda et al. profile →
Dengue virus sero-cross-reactivity drives antibody-dependent enhancement of infection with zika virus

2016 663 citations Wanwisa Dejnirattisai, Piyada Supasa et al. profile →
Original antigenic sin and apoptosis in the pathogenesis of dengue hemorrhagic fever

2003 633 citations Juthathip Mongkolsapaya, Wanwisa Dejnirattisai et al. Nature Medicine profile →
Structural basis of potent Zika–dengue virus antibody cross-neutralization

2016 392 citations Wanwisa Dejnirattisai, Alexander Rouvinski et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gavin Screaton United Kingdom	55	4.6k	4.6k	4.4k	2.7k	1.5k	128	11.8k
Daved H. Fremont United States	75	7.2k 1.6×	3.6k 0.8×	6.1k 1.4×	6.9k 2.5×	2.9k 2.0×	218	17.7k
Mariano A. García-Blanco United States	60	2.4k 0.5×	8.5k 1.8×	2.4k 0.6×	1.4k 0.5×	759 0.5×	195	13.3k
Manuel E. Patarroyo Colombia	61	1.7k 0.4×	5.1k 1.1×	4.9k 1.1×	5.3k 1.9×	2.8k 1.9×	504	14.8k
Andreas Suhrbier Australia	55	3.8k 0.8×	2.1k 0.5×	3.9k 0.9×	2.9k 1.1×	1.9k 1.3×	218	9.4k
Matthew L. Albert France	60	2.5k 0.5×	4.7k 1.0×	2.3k 0.5×	9.1k 3.4×	2.4k 1.7×	151	16.5k
Ali Amara France	47	3.5k 0.8×	1.8k 0.4×	3.0k 0.7×	4.7k 1.7×	1.8k 1.2×	82	10.5k
Wolfgang Garten Germany	59	4.3k 0.9×	2.9k 0.6×	653 0.1×	1.7k 0.6×	4.8k 3.3×	131	10.3k
Bernhard Fleischer Germany	59	2.5k 0.5×	1.9k 0.4×	1.6k 0.4×	5.2k 1.9×	2.8k 1.9×	299	12.0k
Arash Grakoui United States	44	1.5k 0.3×	2.7k 0.6×	1.0k 0.2×	4.1k 1.5×	4.4k 3.1×	101	12.1k
Wayne A. Marasco United States	55	3.8k 0.8×	4.2k 0.9×	670 0.2×	2.7k 1.0×	2.2k 1.5×	165	11.3k

Countries citing papers authored by Gavin Screaton

Since Specialization

Citations

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

Fields of papers citing papers by Gavin Screaton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gavin Screaton

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

Liu, Chang, Xianglin Ji, Yun Wang, et al.. (2025). Engineering Genome‐Free Bacterial Cells for Effective SARS ‐ COV ‐2 Neutralisation. Microbial Biotechnology. 18(3). e70109–e70109.

Asor, Roi, Anna Olerinyova, Sean A. Burnap, et al.. (2024). Cooperativity and induced oligomerization control the interaction of SARS-CoV-2 with its cellular receptor and patient-derived antibodies. Biophysical Journal. 123(3). 313a–313a. 1 indexed citations

Liu, Chang, Raksha Das, Aiste Dijokaite-Guraliuc, et al.. (2024). Emerging variants develop total escape from potent monoclonal antibodies induced by BA.4/5 infection. Nature Communications. 15(1). 3284–3284. 11 indexed citations

Thursz, Mark, Fouzia Sadiq, Julia A. Tree, et al.. (2023). Inhibition of phosphodiesterase 12 results in antiviral activity against several RNA viruses including SARS-CoV-2. Journal of General Virology. 104(7). 1 indexed citations

Chenthamarakshan, Vijil, Samuel C. Hoffman, David Owen, et al.. (2023). Accelerating drug target inhibitor discovery with a deep generative foundation model. Science Advances. 9(25). eadg7865–eadg7865. 22 indexed citations

Prince, Tessa, Xiaofeng Dong, Rebekah Penrice-Randal, et al.. (2022). Analysis of SARS-CoV-2 in Nasopharyngeal Samples from Patients with COVID-19 Illustrates Population Variation and Diverse Phenotypes, Placing the Growth Properties of Variants of Concern in Context with Other Lineages. mSphere. 7(3). e0091321–e0091321. 5 indexed citations

Eyre, David W., Sheila Lumley, Denise O’Donnell, et al.. (2021). Stringent thresholds in SARS-CoV-2 IgG assays lead to under-detection of mild infections. BMC Infectious Diseases. 21(1). 187–187. 19 indexed citations

Sharma, Arvind, Xiaokang Zhang, Wanwisa Dejnirattisai, et al.. (2021). The epitope arrangement on flavivirus particles contributes to Mab C10’s extraordinary neutralization breadth across Zika and dengue viruses. Cell. 184(25). 6052–6066.e18. 50 indexed citations

Abbink, Peter, Rafael A. Larocca, Wanwisa Dejnirattisai, et al.. (2018). Therapeutic and protective efficacy of a dengue antibody against Zika infection in rhesus monkeys. Nature Medicine. 24(6). 721–723. 32 indexed citations

10.

Roberts, Catherine, Juthathip Mongkolsapaya, & Gavin Screaton. (2012). Dengue fever: a practical guide. British Journal of Hospital Medicine. 73(4). C60–C64. 1 indexed citations

11.

Watson, Aleksandra A., Andrey A. Lebedev, Benjamin A. Hall, et al.. (2011). Structural Flexibility of the Macrophage Dengue Virus Receptor CLEC5A. Journal of Biological Chemistry. 286(27). 24208–24218. 42 indexed citations

12.

Newsom-Davis, Thomas, Guoyin Wang, Lawrence Steinman, et al.. (2009). Enhanced Immune Recognition of Cryptic Glycan Markers in Human Tumors. Cancer Research. 69(5). 2018–2025. 39 indexed citations

13.

Li, Demin, Lili Wang, Li Yu, et al.. (2009). Ig-Like Transcript 4 Inhibits Lipid Antigen Presentation through Direct CD1d Interaction. The Journal of Immunology. 182(2). 1033–1040. 37 indexed citations

14.

Wu, Hao, Huiping Yan, Shiwu Ma, et al.. (2008). T Cell Responses to Whole SARS Coronavirus in Humans. The Journal of Immunology. 181(8). 5490–5500. 365 indexed citations

15.

Mongkolsapaya, Juthathip, Thaneeya Duangchinda, Wanwisa Dejnirattisai, et al.. (2006). T Cell Responses in Dengue Hemorrhagic Fever: Are Cross-Reactive T Cells Suboptimal?. The Journal of Immunology. 176(6). 3821–3829. 207 indexed citations

16.

Drakesmith, Hal, et al.. (2005). HIV-1 Nef down-regulates the hemochromatosis protein HFE, manipulating cellular iron homeostasis. Proceedings of the National Academy of Sciences. 102(31). 11017–11022. 69 indexed citations

17.

Chen, Nan, Corinna McCarthy, Hal Drakesmith, et al.. (2005). HIV‐1 down‐regulates the expression of CD1d via Nef. European Journal of Immunology. 36(2). 278–286. 104 indexed citations

18.

Dong, Tao, Guillaume Stewart-Jones, Nan Chen, et al.. (2004). HIV-specific Cytotoxic T Cells from Long-Term Survivors Select a Unique T Cell Receptor. The Journal of Experimental Medicine. 200(12). 1547–1557. 91 indexed citations

19.

Cowper, Alison E., et al.. (1998). Influence of Intron Length on Alternative Splicing of CD44. Molecular and Cellular Biology. 18(10). 5930–5941. 71 indexed citations

20.

Mongkolsapaya, Juthathip, Alison E. Cowper, Xiao‐Ning Xu, et al.. (1998). Cutting Edge: Lymphocyte Inhibitor of TRAIL (TNF-Related Apoptosis-Inducing Ligand): A New Receptor Protecting Lymphocytes from the Death Ligand TRAIL. The Journal of Immunology. 160(1). 3–6. 103 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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