Mathieu Danoy
Impact in
- Hepatology top 5%
- Liver physiology and pathology
-
- 3D Printing in Biomedical Research
- Innovative Microfluidic and Catalytic Techniques Innovation
Papers in
- Hepatology 22
- Liver physiology and pathology 22
-
- 3D Printing in Biomedical Research 21
- Co-authors
- Yasuyuki Sakai (29 shared papers)Marie Shinohara (14 shared papers)Éric Leclerc (22 shared papers)Atsushi Miyajima (19 shared papers)Taketomo Kido (18 shared papers)Rachid Jellali (11 shared papers)Yasuyuki Sakai (5 shared papers)Stéphane Poulain (15 shared papers)
- Journals
- Biotechnology and Bioengineering (5 papers)Biochemical Engineering Journal (4 papers)Differentiation (3 papers)Biotechnology Progress (2 papers)Molecular and Cellular Endocrinology (2 papers)
- Partner nations
- JapanFranceUnited States
In The Last Decade
Mathieu Danoy
34 papers receiving 367 citations
Peers
Comparison fields: 5 of 51
- Hepatology 136
- Biomedical Engineering 209
- Surgery 121
- Molecular Biology 129
- Cellular and Molecular Neuroscience 29
Countries citing papers authored by Mathieu Danoy
This map shows the geographic impact of Mathieu Danoy'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 Mathieu Danoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathieu Danoy more than expected).
Fields of papers citing papers by Mathieu Danoy
This network shows the impact of papers produced by Mathieu Danoy. 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 Mathieu Danoy. The network helps show where Mathieu Danoy may publish in the future.
Co-authors
The 25 scholars most cited alongside Mathieu Danoy, 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 | 2020 | 52 | |
| 2 | 2019 | 28 | |
| 3 | 2020 | 27 | |
| 4 | 2019 | 23 | |
| 5 | 2020 | 22 | |
| 6 | 2016 | 20 | |
| 7 | 2018 | 16 | |
| 8 | 2020 | 14 | |
| 9 | 2021 | 13 | |
| 10 | 2022 | 13 | |
| 11 | 2022 | 13 | |
| 12 | 2020 | 11 | |
| 13 | 2019 | 11 | |
| 14 | 2019 | 10 | |
| 15 | 2021 | 9 | |
| 16 | 2018 | 9 | |
| 17 | 2019 | 8 | |
| 18 | 2017 | 8 | |
| 19 | 2024 | 6 | |
| 20 | 2023 | 6 |
About Mathieu Danoy
Mathieu Danoy is a scholar working on Hepatology, Biomedical Engineering, Surgery, Molecular Biology and Oncology, having authored 34 papers that have together received 368 indexed citations. Recurring topics across this work include Liver physiology and pathology (22 papers), 3D Printing in Biomedical Research (21 papers), Pluripotent Stem Cells Research (13 papers), Pancreatic function and diabetes (13 papers), Tissue Engineering and Regenerative Medicine (4 papers), CRISPR and Genetic Engineering (3 papers), Organ Transplantation Techniques and Outcomes (3 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Hepatology (136 citations), Biomedical Engineering (209 citations), Surgery (121 citations), Molecular Biology (129 citations) and Cellular and Molecular Neuroscience (29 citations). Mathieu Danoy has collaborated with scholars based in Japan, France and United States. Frequent co-authors include Yasuyuki Sakai, Marie Shinohara, Éric Leclerc, Atsushi Miyajima, Taketomo Kido, Rachid Jellali, Yasuyuki Sakai, Stéphane Poulain, Yannick Tauran and Teru Okitsu. Their work appears in journals such as Biotechnology and Bioengineering, Biochemical Engineering Journal, Differentiation, Biotechnology Progress and Molecular and Cellular Endocrinology.
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.