David J. Prieur
- Immunology top 5%
- Molecular Biology
- Genetics top 5%
- Physiology top 10%
- Oncology top 10%
- Co-authors
- Kenneth M. MeyersJames E. TalmadgeJean R. StarkeyLinda L. CollierDavid M. YoungHarry M. OlsonA LeroyReginald L. Reagan
- Topics
- Autoimmune and Inflammatory Disorders Research (21 papers)Lysosomal Storage Disorders Research (20 papers)T-cell and Retrovirus Studies (11 papers)
- Cited by
- ImmunologyMicrobiologyHematology
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
David J. Prieur
112 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Immunology 652
- Molecular Biology 634
- Genetics 375
- Physiology 288
- Oncology 284
Countries citing papers authored by David J. Prieur
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 25 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 12 | |
| 5 | 3 | |
| 6 | 11 | |
| 7 | 9 | |
| 8 | 28 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 18 | |
| 12 | 15 | |
| 13 | 1 | |
| 14 | A skin disorder in three Shetland sheepdogs: comparison with familial canine dermatomyositis of Collies | 14 |
| 15 | 16 | |
| 16 | 10 | |
| 17 | 7 | |
| 18 | 8 | |
| 19 | Hypercalcemia of malignancy. Animal model: VX-2 carcinoma of rabbits. | 3 |
| 20 | The Chediak-Higashi syndrome of cats. | 73 |
About David J. Prieur
David J. Prieur is a scholar working on Hematology, Immunology and Microbiology, having authored 113 papers that have together received 2.3k indexed citations. Recurring topics across this work include Autoimmune and Inflammatory Disorders Research (21 papers), Lysosomal Storage Disorders Research (20 papers) and T-cell and Retrovirus Studies (11 papers). The work is most often cited by research in Immunology (652 citations), Microbiology (152 citations) and Hematology (253 citations). David J. Prieur has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Kenneth M. Meyers, James E. Talmadge, Jean R. Starkey, Linda L. Collier, David M. Young, Harry M. Olson, A Leroy, Reginald L. Reagan, A. M. Hargis and Robert D. Murnane. Their work appears in journals such as Nature, The Journal of Immunology and JNCI Journal of the National Cancer Institute.
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.