Renaud Du Pasquier
- Pathology and Forensic Medicine top 0.5%
- Oncology top 1%
- Immunology top 1%
- Molecular Biology top 10%
- Neurology top 1%
- Co-authors
- Igor J. KoralnikMyriam SchluepGiuseppe PantaleoAmandine MathiasSamantha JilekMathieu CanalesGreta GuardaMatthias Cavassini
- Topics
- Multiple Sclerosis Research Studies (53 papers)Polyomavirus and related diseases (47 papers)HIV Research and Treatment (26 papers)
- Partner nations
- SwitzerlandUnited StatesFrance
In The Last Decade
Renaud Du Pasquier
188 papers receiving 7.2k citations
Hit Papers
Peers
Comparison fields: 5 of 154
- Pathology and Forensic Medicine 1.8k
- Oncology 1.7k
- Immunology 1.6k
- Molecular Biology 1.2k
- Neurology 1.2k
Countries citing papers authored by Renaud Du Pasquier
This map shows the geographic impact of Renaud Du Pasquier'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 Renaud Du Pasquier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Renaud Du Pasquier more than expected).
Fields of papers citing papers by Renaud Du Pasquier
This network shows the impact of papers produced by Renaud Du Pasquier. 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 Renaud Du Pasquier. The network helps show where Renaud Du Pasquier may publish in the future.
Co-authorship network of co-authors of Renaud Du Pasquier
This figure shows the co-authorship network connecting the top 25 collaborators of Renaud Du Pasquier. A scholar is included among the top collaborators of Renaud Du Pasquier 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 Renaud Du Pasquier. Renaud Du Pasquier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 20 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 17 | |
| 6 | 20 | |
| 7 | 84 | |
| 8 | 9 | |
| 9 | 28 | |
| 10 | 27 | |
| 11 | 106 | |
| 12 | 43 | |
| 13 | 111 | |
| 14 | 128 | |
| 15 | 54 | |
| 16 | Differential diagnosis of multiple sclerosis with machine learning-based central vein sign recognition | 1 |
| 17 | 2 | |
| 18 | 3 | |
| 19 | Nouveau spectre des troubles cognitifs liés à l'infection par le VIH à l'ère des trithérapies | 1 |
| 20 | 14 |
About Renaud Du Pasquier
Renaud Du Pasquier is a scholar working on Virology, Pathology and Forensic Medicine and Neurology, having authored 201 papers that have together received 7.3k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (53 papers), Polyomavirus and related diseases (47 papers) and HIV Research and Treatment (26 papers). The work is most often cited by research in Virology (716 citations), Pathology and Forensic Medicine (1.8k citations) and Neurology (1.2k citations). Renaud Du Pasquier has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Igor J. Koralnik, Myriam Schluep, Giuseppe Pantaleo, Amandine Mathias, Samantha Jilek, Mathieu Canales, Greta Guarda, Matthias Cavassini, P Druet and Lucette Pelletier. Their work appears in journals such as Journal of Clinical Investigation, The Journal of Experimental Medicine and Immunity.
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.