Nicholas Davis‐Poynter

4.9k total citations
71 papers, 3.9k citations indexed

About

Nicholas Davis‐Poynter is a scholar working on Epidemiology, Immunology and Genetics. According to data from OpenAlex, Nicholas Davis‐Poynter has authored 71 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Epidemiology, 29 papers in Immunology and 9 papers in Genetics. Recurrent topics in Nicholas Davis‐Poynter's work include Cytomegalovirus and herpesvirus research (44 papers), Herpesvirus Infections and Treatments (38 papers) and Immune Cell Function and Interaction (18 papers). Nicholas Davis‐Poynter is often cited by papers focused on Cytomegalovirus and herpesvirus research (44 papers), Herpesvirus Infections and Treatments (38 papers) and Immune Cell Function and Interaction (18 papers). Nicholas Davis‐Poynter collaborates with scholars based in Australia, United Kingdom and United States. Nicholas Davis‐Poynter's co-authors include Helen E. Farrell, Tony Minson, Helena Browne, Susanne Bell, Hassan Vally, A. C. Minson, Gavin W. G. Wilkinson, J. F. Kaye, Stuart B. Mazzone and Alice E. McGovern and has published in prestigious journals such as Nature, The Journal of Experimental Medicine and Journal of Neuroscience.

In The Last Decade

Nicholas Davis‐Poynter

71 papers receiving 3.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicholas Davis‐Poynter Australia 31 2.8k 1.4k 525 406 405 71 3.9k
Herman W. Favoreel Belgium 40 1.9k 0.7× 1.2k 0.9× 807 1.5× 369 0.9× 317 0.8× 158 4.3k
Claude Krummenacher United States 37 3.6k 1.3× 1.5k 1.1× 1.2k 2.3× 225 0.6× 455 1.1× 65 4.6k
H. Ludwig Germany 40 4.0k 1.4× 540 0.4× 663 1.3× 274 0.7× 495 1.2× 136 4.8k
Aidan Dolan United Kingdom 26 4.8k 1.7× 978 0.7× 1.2k 2.3× 615 1.5× 901 2.2× 32 5.4k
Laurent Gillet Belgium 31 1.4k 0.5× 1.1k 0.8× 298 0.6× 188 0.5× 748 1.8× 121 3.2k
Bernhard Ehlers Germany 36 2.0k 0.7× 536 0.4× 525 1.0× 374 0.9× 1.6k 3.9× 94 4.3k
Peter A. Barry United States 39 2.7k 1.0× 996 0.7× 558 1.1× 478 1.2× 344 0.8× 118 4.3k
Anders Vahlne Sweden 35 1.7k 0.6× 979 0.7× 424 0.8× 102 0.3× 295 0.7× 119 3.7k
J G Stevens United States 33 3.7k 1.3× 985 0.7× 1.1k 2.0× 229 0.6× 281 0.7× 58 4.1k
Barbara G. Klupp Germany 51 5.9k 2.1× 1.4k 1.0× 1.1k 2.1× 980 2.4× 803 2.0× 146 7.0k

Countries citing papers authored by Nicholas Davis‐Poynter

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Davis‐Poynter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicholas Davis‐Poynter. 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 Nicholas Davis‐Poynter. The network helps show where Nicholas Davis‐Poynter may publish in the future.

Co-authorship network of co-authors of Nicholas Davis‐Poynter

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

All Works

20 of 20 papers shown
1.
Stanfield, Brent, et al.. (2022). The CMV-encoded G protein-coupled receptors M33 and US28 play pleiotropic roles in immune evasion and alter host T cell responses. Frontiers in Immunology. 13. 1047299–1047299. 8 indexed citations
2.
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Yunis, Joseph, Helen E. Farrell, Kimberley Bruce, et al.. (2018). Murine cytomegalovirus degrades MHC class II to colonize the salivary glands. PLoS Pathogens. 14(2). e1006905–e1006905. 27 indexed citations
4.
5.
Farrell, Helen E., Kimberley Bruce, Clara Lawler, et al.. (2017). Murine Cytomegalovirus Spreads by Dendritic Cell Recirculation. mBio. 8(5). 58 indexed citations
6.
McGovern, Alice E., Nicholas Davis‐Poynter, Michael J. Farrell, & Stuart B. Mazzone. (2012). Transneuronal tracing of airways-related sensory circuitry using herpes simplex virus 1, strain H129. Neuroscience. 207. 148–166. 71 indexed citations
7.
McGovern, Alice E., et al.. (2012). Anterograde neuronal circuit tracing using a genetically modified herpes simplex virus expressing EGFP. Journal of Neuroscience Methods. 209(1). 158–167. 55 indexed citations
8.
Lunn, D.P., Nicholas Davis‐Poynter, M. Julia B.F. Flaminio, et al.. (2009). Equine Herpesvirus-1 Consensus Statement. Journal of Veterinary Internal Medicine. 23(3). 450–461. 230 indexed citations
9.
Sharp, Emma L., Nicholas Davis‐Poynter, & Helen E. Farrell. (2008). Analysis of the subcellular trafficking properties of murine cytomegalovirus M78, a 7 transmembrane receptor homologue. Journal of General Virology. 90(1). 59–68. 15 indexed citations
10.
Robinson, Carl, Iain C. Sutcliffe, Josh Slater, et al.. (2006). Mutation of the Maturase Lipoprotein Attenuates the Virulence ofStreptococcus equito a Greater Extent than Does Loss of General Lipoprotein Lipidation. Infection and Immunity. 74(12). 6907–6919. 50 indexed citations
11.
Paillot, Romain, Janet M. Daly, Richard Luce, et al.. (2006). Frequency and phenotype of EHV-1 specific, IFN-γ synthesising lymphocytes in ponies: The effects of age, pregnancy and infection. Developmental & Comparative Immunology. 31(2). 202–214. 28 indexed citations
12.
Šmid, Lojze, et al.. (2005). Use of polarised equine endothelial cell cultures and an in vitro thrombosis model for potential characterisation of EHV-1 strain variation. Veterinary Microbiology. 113(3-4). 243–249. 8 indexed citations
13.
Smith, Ken, et al.. (2003). In vitro characterisation of high and low virulence isolates of equine herpesvirus-1 and -4. Research in Veterinary Science. 75(1). 83–86. 26 indexed citations
14.
Daly, Janet M., Philip Yates, J. R. Newton, et al.. (2003). Comparison of hamster and pony challenge models for evaluation of effect of antigenic drift on cross protection afforded by equine influenza vaccines. Equine Veterinary Journal. 35(5). 458–462. 35 indexed citations
15.
Castillo‐Olivares, Javier, et al.. (2003). Detection of equine arteritis virus (EAV)-specific cytotoxic CD8+ T lymphocyte precursors from EAV-infected ponies. Journal of General Virology. 84(10). 2745–2753. 17 indexed citations
16.
Birch‐Machin, Ian, Stephen Ryder, Louise Taylor, et al.. (2000). Utilisation of bacteriophage display libraries to identify peptide sequences recognised by Equine herpesvirus type 1 specific equine sera. Journal of Virological Methods. 88(1). 89–104. 8 indexed citations
17.
Cretney, Erika, et al.. (1999). M144, a Murine Cytomegalovirus (Mcmv)-Encoded Major Histocompatibility Complex Class I Homologue, Confers Tumor Resistance to Natural Killer Cell–Mediated Rejection. The Journal of Experimental Medicine. 190(3). 435–444. 63 indexed citations
18.
Davis‐Poynter, Nicholas, Mariapia A. Degli‐Esposti, & Helen E. Farrell. (1999). Murine Cytomegalovirus Homologues of Cellular Immunomodulatory Genes. Intervirology. 42(5-6). 331–341. 10 indexed citations
19.
20.
Hutchinson, Lloyd, Helena Browne, Nicholas Davis‐Poynter, et al.. (1992). A novel herpes simplex virus glycoprotein, gL, forms a complex with glycoprotein H (gH) and affects normal folding and surface expression of gH. Journal of Virology. 66(4). 2240–2250. 283 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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