Joan Font-Burgada
- Molecular Biology top 10%
- Oncology top 5%
- Immunology top 5%
- Epidemiology top 5%
- Cancer Research top 5%
- Co-authors
- Michael KarinBeicheng SunHayato NakagawaDebanjan DharHannah CarterShabnam ShalapourKoji TaniguchiAtsushi Umemura
- Topics
- Immunotherapy and Immune Responses (5 papers)Liver Disease Diagnosis and Treatment (4 papers)vaccines and immunoinformatics approaches (4 papers)
- Cited by
- HepatologyImmunologyCancer Research
- Partner nations
- United StatesSpainJapan
In The Last Decade
Joan Font-Burgada
20 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Molecular Biology 1.0k
- Oncology 852
- Immunology 799
- Epidemiology 587
- Cancer Research 506
Countries citing papers authored by Joan Font-Burgada
This map shows the geographic impact of Joan Font-Burgada'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 Joan Font-Burgada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Font-Burgada more than expected).
Fields of papers citing papers by Joan Font-Burgada
This network shows the impact of papers produced by Joan Font-Burgada. 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 Joan Font-Burgada. The network helps show where Joan Font-Burgada may publish in the future.
Co-authorship network of co-authors of Joan Font-Burgada
This figure shows the co-authorship network connecting the top 25 collaborators of Joan Font-Burgada. A scholar is included among the top collaborators of Joan Font-Burgada 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 Joan Font-Burgada. Joan Font-Burgada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 13 | |
| 3 | 2 | |
| 4 | 19 | |
| 5 | 33 | |
| 6 | 157 | |
| 7 | 61 | |
| 8 | 225 | |
| 9 | 4 | |
| 10 | 275 | |
| 11 | Immunosuppressive plasma cells impede T-cell-dependent immunogenic chemotherapybreakdown → | 429 |
| 12 | 22 | |
| 13 | Hybrid Periportal Hepatocytes Regenerate the Injured Liver without Giving Rise to Cancerbreakdown → | 361 |
| 14 | 16 | |
| 15 | 95 | |
| 16 | ER Stress Cooperates with Hypernutrition to Trigger TNF-Dependent Spontaneous HCC Developmentbreakdown → | 396 |
| 17 | 91 | |
| 18 | 358 | |
| 19 | 2 | |
| 20 | 55 |
About Joan Font-Burgada
Joan Font-Burgada is a scholar working on Hepatology, Immunology and Cancer Research, having authored 20 papers that have together received 2.6k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (5 papers), Liver Disease Diagnosis and Treatment (4 papers) and vaccines and immunoinformatics approaches (4 papers). The work is most often cited by research in Hepatology (493 citations), Immunology (799 citations) and Cancer Research (506 citations). Joan Font-Burgada has collaborated with scholars based in United States, Spain and Japan. Frequent co-authors include Michael Karin, Beicheng Sun, Hayato Nakagawa, Debanjan Dhar, Hannah Carter, Shabnam Shalapour, Koji Taniguchi, Atsushi Umemura, David Rossell and Zhenyu Zhong. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.