Xiao-Ning Xu

2.4k total citations · 1 hit paper
7 papers, 1.7k citations indexed

About

Xiao-Ning Xu is a scholar working on Immunology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Xiao-Ning Xu has authored 7 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Immunology, 3 papers in Infectious Diseases and 3 papers in Epidemiology. Recurrent topics in Xiao-Ning Xu's work include Influenza Virus Research Studies (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Respiratory viral infections research (2 papers). Xiao-Ning Xu is often cited by papers focused on Influenza Virus Research Studies (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Respiratory viral infections research (2 papers). Xiao-Ning Xu collaborates with scholars based in United Kingdom, United States and Taiwan. Xiao-Ning Xu's co-authors include Andrew J. McMichael, Gavin Screaton, Daniel C. Douek, Tao Dong, Tom Wilkinson, Cecilia Chui, Rob Lambkin‐Williams, John Oxford, Anthony Gilbert and Molly Perkins and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and The Journal of Experimental Medicine.

In The Last Decade

Xiao-Ning Xu

7 papers receiving 1.6k citations

Hit Papers

Preexisting influenza-specific CD4+ T cells correlate wit... 2012 2026 2016 2021 2012 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiao-Ning Xu United Kingdom 7 853 679 676 371 153 7 1.7k
K. Kai McKinstry United States 20 1.6k 1.9× 767 1.1× 399 0.6× 286 0.8× 105 0.7× 22 2.3k
Sophie A. Valkenburg Hong Kong 26 1.0k 1.2× 1.1k 1.7× 801 1.2× 518 1.4× 38 0.2× 62 2.3k
Bobo Wing-Yee Mok Hong Kong 22 346 0.4× 425 0.6× 697 1.0× 451 1.2× 45 0.3× 34 1.5k
Kurt H. Edelmann United States 11 1.0k 1.2× 504 0.7× 380 0.6× 220 0.6× 89 0.6× 16 1.7k
Adam J. Hume United States 19 233 0.3× 452 0.7× 778 1.2× 315 0.8× 79 0.5× 38 1.3k
Yasushi Muraki Japan 26 404 0.5× 1.3k 1.9× 421 0.6× 500 1.3× 47 0.3× 79 1.7k
Branka Grubor‐Bauk Australia 17 482 0.6× 360 0.5× 282 0.4× 265 0.7× 127 0.8× 41 1.1k
Gaurav D. Gaiha United States 15 677 0.8× 270 0.4× 598 0.9× 461 1.2× 505 3.3× 28 1.4k
Yean K. Yong Malaysia 19 503 0.6× 354 0.5× 426 0.6× 190 0.5× 156 1.0× 49 1.2k
Jesper Melchjorsen Denmark 26 1.4k 1.6× 818 1.2× 521 0.8× 564 1.5× 468 3.1× 35 2.3k

Countries citing papers authored by Xiao-Ning Xu

Since Specialization
Citations

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

Fields of papers citing papers by Xiao-Ning Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao-Ning Xu. 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 Xiao-Ning Xu. The network helps show where Xiao-Ning Xu may publish in the future.

Co-authorship network of co-authors of Xiao-Ning Xu

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

All Works

7 of 7 papers shown
1.
Clutterbuck, Elizabeth, Cecilia Chui, Tom Wilkinson, et al.. (2014). Virus-Specific Antibody Secreting Cell, Memory B-cell, and Sero-Antibody Responses in the Human Influenza Challenge Model. The Journal of Infectious Diseases. 209(9). 1354–1361. 43 indexed citations
2.
Wilkinson, Tom, Cecilia Chui, Ang Huang, et al.. (2012). Preexisting influenza-specific CD4+ T cells correlate with disease protection against influenza challenge in humans. Nature Medicine. 18(2). 274–280. 766 indexed citations breakdown →
3.
Freundt, Eric C., Li Yu, Cynthia S. Goldsmith, et al.. (2009). The Open Reading Frame 3a Protein of Severe Acute Respiratory Syndrome-Associated Coronavirus Promotes Membrane Rearrangement and Cell Death. Journal of Virology. 84(2). 1097–1109. 103 indexed citations
4.
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
5.
Xu, Xiao-Ning, Nan Chen, Jennifer H. Cox, et al.. (2001). A Novel Approach to Antigen-Specific Deletion of CTL with Minimal Cellular Activation Using α3 Domain Mutants of MHC Class I/Peptide Complex. Immunity. 14(5). 591–602. 63 indexed citations
6.
Screaton, Gavin, Xiao-Ning Xu, Anna L Olsen, et al.. (1997). LARD: A new lymphoid-specific death domain containing receptor regulated by alternative pre-mRNA splicing. Proceedings of the National Academy of Sciences. 94(9). 4615–4619. 184 indexed citations
7.
Xu, Xiao-Ning, Gavin Screaton, Frances Gotch, et al.. (1997). Evasion of Cytotoxic T Lymphocyte (CTL) Responses by Nef-dependent Induction of Fas Ligand (CD95L) Expression on Simian Immunodeficiency Virus–infected Cells. The Journal of Experimental Medicine. 186(1). 7–16. 166 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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