Khadir Raddassi
Impact in
- Developmental Neuroscience top 0.5%
- Neurogenesis and neuroplasticity mechanisms
- Neurology top 1%
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
- Immunology 28
- Immune Cell Function and Interaction 14
- T-cell and B-cell Immunology 11
- Immunotherapy and Immune Responses 7
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- Cell Image Analysis Techniques 5
- Co-authors
- Samia J. KhouryDavid A. HaflerJaime ImitolaRichard L. SidmanMarta NietoChristopher A. WalshYang D. TengJianxue Li
- Journals
- Journal of Clinical Investigation (3 papers)Cellular Immunology (2 papers)Clinical Immunology (2 papers)The Journal of Immunology (2 papers)American Journal Of Pathology (2 papers)
- Partner nations
- United StatesFranceJapan
In The Last Decade
Khadir Raddassi
47 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Developmental Neuroscience 739
- Neurology 685
- Immunology 1.4k
- Genetics 449
- Biological Psychiatry 63
Countries citing papers authored by Khadir Raddassi
This map shows the geographic impact of Khadir Raddassi'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 Khadir Raddassi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khadir Raddassi more than expected).
Fields of papers citing papers by Khadir Raddassi
This network shows the impact of papers produced by Khadir Raddassi. 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 Khadir Raddassi. The network helps show where Khadir Raddassi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Khadir Raddassi, 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 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 6 | |
| 4 | 2021 | 16 | |
| 5 | 2020 | 78 | |
| 6 | 2020 | 45 | |
| 7 | 2019 | 42 | |
| 8 | 2016 | 25 | |
| 9 | Functional inflammatory profiles distinguish myelin-reactive T cells from patients with multiple sclerosis | 2015 | 15 |
| 10 | 2014 | 28 | |
| 11 | 2012 | 23 | |
| 12 | 2012 | 285 | |
| 13 | 2008 | 70 | |
| 14 | 2008 | 54 | |
| 15 | 2007 | 124 | |
| 16 | 1997 | 18 | |
| 17 | 1994 | 70 | |
| 18 | 1993 | 45 | |
| 19 | 1991 | 5 | |
| 20 | 1991 | 24 |
About Khadir Raddassi
Khadir Raddassi is a scholar working on Immunology, Biophysics, Neurology, Biochemistry and Genetics, having authored 49 papers that have together received 3.6k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (14 papers), T-cell and B-cell Immunology (11 papers), Immunotherapy and Immune Responses (7 papers), Single-cell and spatial transcriptomics (6 papers), Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Cell Image Analysis Techniques (5 papers), Cancer Immunotherapy and Biomarkers (5 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). The work is most often cited by research in Developmental Neuroscience (739 citations), Neurology (685 citations), Immunology (1.4k citations), Genetics (449 citations) and Biological Psychiatry (63 citations). Khadir Raddassi has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Samia J. Khoury, David A. Hafler, Jaime Imitola, Richard L. Sidman, Marta Nieto, Christopher A. Walsh, Yang D. Teng, Jianxue Li, Kook In Park and Dan Frenkel. Their work appears in journals such as Journal of Clinical Investigation, Cellular Immunology, Clinical Immunology, The Journal of Immunology and American Journal Of Pathology.
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.