David J. Prieur

127 total papers · 2.9k total citations
113 papers, 2.3k citations indexed

About

David J. Prieur is a scholar working on Molecular Biology, Immunology and Physiology. According to data from OpenAlex, David J. Prieur has authored 113 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 29 papers in Immunology and 25 papers in Physiology. Recurrent topics in David J. Prieur's work include Autoimmune and Inflammatory Disorders Research (21 papers), Lysosomal Storage Disorders Research (20 papers) and Inflammatory Myopathies and Dermatomyositis (11 papers). David J. Prieur is often cited by papers focused on Autoimmune and Inflammatory Disorders Research (21 papers), Lysosomal Storage Disorders Research (20 papers) and Inflammatory Myopathies and Dermatomyositis (11 papers). David J. Prieur collaborates with scholars based in United States, United Kingdom and France. David J. Prieur's co-authors include Kenneth M. Meyers, James E. Talmadge, Jean R. Starkey, Linda L. Collier, David M. Young, Harry M. Olson, Reginald L. Reagan, A Leroy, A. M. Hargis and Robert D. Murnane and has published in prestigious journals such as Nature, The Journal of Immunology and JNCI Journal of the National Cancer Institute.

In The Last Decade

David J. Prieur

112 papers receiving 2.1k citations

Hit Papers

Role of NK cells in tumou... 1980 2026 1995 2010 1980 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David J. Prieur 654 635 375 290 284 113 2.3k
Carl T. Hansen 923 1.4× 960 1.5× 543 1.4× 468 1.6× 239 0.8× 86 3.3k
Matthew F. Starost 391 0.6× 1.3k 2.0× 334 0.9× 185 0.6× 258 0.9× 97 2.4k
Andrea Amalfitano 737 1.1× 833 1.3× 345 0.9× 257 0.9× 387 1.4× 66 2.3k
Yukie Yamaguchi 473 0.7× 485 0.8× 147 0.4× 269 0.9× 158 0.6× 105 2.3k
Vivian Lam 1.1k 1.7× 856 1.3× 293 0.8× 381 1.3× 338 1.2× 55 2.6k
E. J. Eichwald 1.2k 1.8× 649 1.0× 528 1.4× 96 0.3× 250 0.9× 101 3.2k
Jean‐Pierre Louboutin 758 1.2× 925 1.5× 622 1.7× 318 1.1× 199 0.7× 64 2.6k
Nobuhiro Nakano 1.4k 2.2× 792 1.2× 238 0.6× 426 1.5× 496 1.7× 79 3.1k
Susan Kaufman 684 1.0× 1.1k 1.8× 254 0.7× 289 1.0× 554 2.0× 89 3.0k
Cheryl L. Scudamore 921 1.4× 1.0k 1.6× 262 0.7× 231 0.8× 541 1.9× 100 2.8k

Countries citing papers authored by David J. Prieur

Since Specialization
Citations

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

Fields of papers citing papers by David J. Prieur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Prieur. 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 David J. Prieur. The network helps show where David J. Prieur may publish in the future.

Co-authorship network of co-authors of David J. Prieur

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

All Works

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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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