Christophe Parizot
- Immunology top 0.5%
- Immune Cell Function and Interaction 13
- T-cell and B-cell Immunology 10
- Virology top 2%
- HIV Research and Treatment 8
- Rheumatology top 1%
- Systemic Lupus Erythematosus Research 4
- Transplantation top 5%
- Oncology top 5%
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- Chronic Lymphocytic Leukemia Research 5
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- Glycosylation and Glycoproteins Research 4
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- Monoclonal and Polyclonal Antibodies Research 4
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- COVID-19 Clinical Research Studies 3
- Co-authors
- Guy GorochovZahir AmouraMakoto MiyaraPatrice DebréDominique ValeyreAlexis MathianKarim DorghamShimon Sakaguchi
- Cited by
- ImmunologyVirologyRheumatology
- Journals
- Journal of Clinical Investigation (1 paper)Nature Medicine (1 paper)The Journal of Experimental Medicine (2 papers)
- Partner nations
- FranceUnited StatesEstonia
In The Last Decade
Christophe Parizot
48 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Immunology 3.0k
- Virology 365
- Rheumatology 613
- Transplantation 85
- Oncology 702
Countries citing papers authored by Christophe Parizot
This map shows the geographic impact of Christophe Parizot'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 Christophe Parizot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christophe Parizot more than expected).
Fields of papers citing papers by Christophe Parizot
This network shows the impact of papers produced by Christophe Parizot. 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 Christophe Parizot. The network helps show where Christophe Parizot may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Christophe Parizot, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2021 | 22 | |
| 3 | 2021 | 18 | |
| 4 | 2021 | 20 | |
| 5 | 2019 | 6 | |
| 6 | 2015 | 24 | |
| 7 | 2012 | 1 | |
| 8 | 2012 | 114 | |
| 9 | 2011 | 112 | |
| 10 | 2011 | 56 | |
| 11 | 2010 | 158 | |
| 12 | 2009 | 85 | |
| 13 | 2009 | 37 | |
| 14 | Functional Delineation and Differentiation Dynamics of Human CD4+ T Cells Expressing the FoxP3 Transcription Factorbreakdown → | 2009 | 1761 |
| 15 | 2009 | 20 | |
| 16 | 2006 | 337 | |
| 17 | 2005 | 373 | |
| 18 | 2004 | 9 | |
| 19 | 2003 | 150 | |
| 20 | 2003 | 44 |
About Christophe Parizot
Christophe Parizot is a scholar working on Virology, Immunology and Genetics, having authored 49 papers that have together received 4.5k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (13 papers), T-cell and B-cell Immunology (10 papers), HIV Research and Treatment (8 papers), Chronic Lymphocytic Leukemia Research (5 papers), Glycosylation and Glycoproteins Research (4 papers), Systemic Lupus Erythematosus Research (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers) and COVID-19 Clinical Research Studies (3 papers). The work is most often cited by research in Immunology (3.0k citations), Virology (365 citations) and Rheumatology (613 citations). Christophe Parizot has collaborated with scholars based in France, United States and Estonia. Frequent co-authors include Guy Gorochov, Zahir Amoura, Makoto Miyara, Patrice Debré, Dominique Valeyre, Alexis Mathian, Karim Dorgham, Shimon Sakaguchi, Akihiko Kitoh and Takashi Nomura. Their work appears in journals such as Journal of Clinical Investigation, Nature Medicine and The Journal of Experimental Medicine.
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.