Hsin-Jung Wu
- Molecular Biology top 5%
- Immunology top 2%
- Infectious Diseases top 2%
- Genetics top 5%
- Physiology top 5%
- Co-authors
- Eric WuDiane MathisChristophe BenoıstDan R. LittmanKimie HattoriTatsuichiro ShimaJaime DarceYoshinori Umesaki
- Topics
- Immune Cell Function and Interaction (8 papers)Immunotherapy and Immune Responses (6 papers)T-cell and B-cell Immunology (6 papers)
- Journals
- Proceedings of the National Academy of SciencesThe Journal of Experimental MedicineImmunity
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Hsin-Jung Wu
20 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Molecular Biology 2.1k
- Immunology 1.1k
- Infectious Diseases 845
- Genetics 603
- Physiology 427
Countries citing papers authored by Hsin-Jung Wu
This map shows the geographic impact of Hsin-Jung Wu'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 Hsin-Jung Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsin-Jung Wu more than expected).
Fields of papers citing papers by Hsin-Jung Wu
This network shows the impact of papers produced by Hsin-Jung Wu. 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 Hsin-Jung Wu. The network helps show where Hsin-Jung Wu may publish in the future.
Co-authorship network of co-authors of Hsin-Jung Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Hsin-Jung Wu. A scholar is included among the top collaborators of Hsin-Jung Wu 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 Hsin-Jung Wu. Hsin-Jung Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | The gut–joint axis in rheumatoid arthritisbreakdown → | 246 |
| 3 | 7 | |
| 4 | 147 | |
| 5 | 26 | |
| 6 | Identifying species of symbiont bacteria from the human gut that, alone, can induce intestinal Th17 cells in micebreakdown → | 324 |
| 7 | 2 | |
| 8 | 20 | |
| 9 | 20 | |
| 10 | The role of gut microbiota in immune homeostasis and autoimmunitybreakdown → | 1009 |
| 11 | 340 | |
| 12 | Gut-Residing Segmented Filamentous Bacteria Drive Autoimmune Arthritis via T Helper 17 Cellsbreakdown → | 1198 |
| 13 | 59 | |
| 14 | 38 | |
| 15 | 83 | |
| 16 | 77 | |
| 17 | 25 | |
| 18 | 17 | |
| 19 | 21 | |
| 20 | 42 |
About Hsin-Jung Wu
Hsin-Jung Wu is a scholar working on Immunology, Urology and Infectious Diseases, having authored 20 papers that have together received 3.7k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (8 papers), Immunotherapy and Immune Responses (6 papers) and T-cell and B-cell Immunology (6 papers). The work is most often cited by research in Biological Psychiatry (181 citations), Gastroenterology (333 citations) and Immunology (1.1k citations). Hsin-Jung Wu has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Eric Wu, Diane Mathis, Christophe Benoıst, Dan R. Littman, Kimie Hattori, Tatsuichiro Shima, Jaime Darce, Yoshinori Umesaki, Ivaylo I. Ivanov and Esen Sefik. Their work appears in journals such as Proceedings of the National Academy of Sciences, 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.