Raphaël Lis
Impact in
- Hepatology top 5%
- Liver physiology and pathology
- Cell Biology top 5%
- Zebrafish Biomedical Research Applications
Papers in
- Cell Biology 10
- Zebrafish Biomedical Research Applications 8
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- Hematopoietic Stem Cell Transplantation 7
- Co-authors
- Shahin Rafii (26 shared papers)Koji Shido (8 shared papers)Sina Y. Rabbany (7 shared papers)Bi‐Sen Ding (7 shared papers)Zhongwei Cao (3 shared papers)Peipei Guo (4 shared papers)Michael Simons (1 shared paper)Mark E.T. Penfold (1 shared paper)
- Journals
- Blood (4 papers)Nature Communications (3 papers)Nature (3 papers)Experimental Hematology (2 papers)Nature Cell Biology (2 papers)
- Partner nations
- United StatesQatarFrance
In The Last Decade
Raphaël Lis
33 papers receiving 2.2k citations
Raphaël Lis's Hit Papers
Peers
Comparison fields: 5 of 96
- Hepatology 289
- Cell Biology 417
- Hematology 211
- Immunology 364
- Neurology 133
Countries citing papers authored by Raphaël Lis
This map shows the geographic impact of Raphaël Lis'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 Raphaël Lis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Lis more than expected).
Fields of papers citing papers by Raphaël Lis
This network shows the impact of papers produced by Raphaël Lis. 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 Raphaël Lis. The network helps show where Raphaël Lis may publish in the future.
Co-authors
The 25 scholars most cited alongside Raphaël Lis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Divergent angiocrine signals from vascular niche balance liver regeneration and fibrosis Hit paper breakdown → | 2013 | 529 |
| 2 | 2016 | 231 | |
| 3 | 2014 | 188 | |
| 4 | 2021 | 168 | |
| 5 | 2017 | 166 | |
| 6 | 2015 | 153 | |
| 7 | 2015 | 132 | |
| 8 | 2019 | 98 | |
| 9 | 2012 | 80 | |
| 10 | 2018 | 68 | |
| 11 | 2013 | 66 | |
| 12 | 2017 | 59 | |
| 13 | 2018 | 54 | |
| 14 | 2022 | 49 | |
| 15 | 2021 | 42 | |
| 16 | 2021 | 34 | |
| 17 | 2014 | 32 | |
| 18 | 2024 | 21 | |
| 19 | 2019 | 19 | |
| 20 | 2017 | 18 |
About Raphaël Lis
Raphaël Lis is a scholar working on Cell Biology, Hematology, Immunology, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 34 papers that have together received 2.3k indexed citations. Recurring topics across this work include Zebrafish Biomedical Research Applications (8 papers), Hematopoietic Stem Cell Transplantation (7 papers), Pluripotent Stem Cells Research (5 papers), Neonatal Respiratory Health Research (4 papers), Single-cell and spatial transcriptomics (4 papers), Renal and related cancers (4 papers), CRISPR and Genetic Engineering (2 papers) and Diabetes and associated disorders (2 papers). The work is most often cited by research in Hepatology (289 citations), Cell Biology (417 citations), Hematology (211 citations), Immunology (364 citations) and Neurology (133 citations). Raphaël Lis has collaborated with scholars based in United States, Qatar and France. Frequent co-authors include Shahin Rafii, Koji Shido, Sina Y. Rabbany, Bi‐Sen Ding, Zhongwei Cao, Peipei Guo, Michael Simons, Mark E.T. Penfold, Daniel J. Nolan and Deebly Chavez. Their work appears in journals such as Blood, Nature Communications, Nature, Experimental Hematology and Nature Cell Biology.
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.