William Lees

1.1k citations
36 papers · 430 · h-index 12

Impact in

Papers in

    • T-cell and B-cell Immunology 18
    • Immune Cell Function and Interaction 14
    • Glycosylation and Glycoproteins Research 7
    • Single-cell and spatial transcriptomics 6
    • vaccines and immunoinformatics approaches 6

William Lees

35 papers receiving 421 citations

Peers

William Lees
Comparison fields: 5 of 46
  • Immunology 228
  • Radiology, Nuclear Medicine and Imaging 146
  • Virology 17
  • Hepatology 26
  • Epidemiology 102
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Shuaiyi Liang China
Sneha Rangarajan United States
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James Testa United States
Gérard Somme France
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Noëlle Doyen France
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Citations per field
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Citations per year

Countries citing papers authored by William Lees

Since Specialization
Citations

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

Fields of papers citing papers by William Lees

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside William Lees, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with William Lees Line = papers co-authored together William Lees links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201045
2 201943
3 201941
4 201939
5 202230
6 202026
7 202019
8 201918
9 202417
10 202215
11 202312
12 202411
13 201411
14 202310
15 20119
16 20229
17 20159
18 20179
19 20179
20 20138

About William Lees

William Lees is a scholar working on Immunology, Molecular Biology, Radiology, Nuclear Medicine and Imaging, Epidemiology and Hematology, having authored 36 papers that have together received 430 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (18 papers), Monoclonal and Polyclonal Antibodies Research (15 papers), Immune Cell Function and Interaction (14 papers), Glycosylation and Glycoproteins Research (7 papers), Single-cell and spatial transcriptomics (6 papers), Influenza Virus Research Studies (6 papers), vaccines and immunoinformatics approaches (6 papers) and Blood groups and transfusion (3 papers). The work is most often cited by research in Immunology (228 citations), Radiology, Nuclear Medicine and Imaging (146 citations), Virology (17 citations), Hepatology (26 citations) and Epidemiology (102 citations). William Lees has collaborated with scholars based in United Kingdom, United States and Israel. Frequent co-authors include Adrian J. Shepherd, David S. Moss, Gur Yaari, Corey T. Watson, Andrew M. Collins, Ayelet Peres, Mats Ohlin, Pazit Polak, Martin Corcoran and Oscar L. Rodriguez. Their work appears in journals such as Frontiers in Immunology, Nucleic Acids Research, Bioinformatics, Journal of Virology and Current Opinion in Systems Biology.

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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