Di Fu
Impact in
- Biochemistry top 2%
- Sulfur Compounds in Biology
-
- Lymphoma Diagnosis and Treatment
Papers in
-
- Cancer-related gene regulation 5
- Insect Resistance and Genetics 4
-
- Lymphoma Diagnosis and Treatment 20
- Co-authors
- Shabbir Moochhala (1 shared paper)Philip K. Moore (1 shared paper)Madhav Bhatia (1 shared paper)Li Wang (17 shared papers)Pengpeng Xu (17 shared papers)Shu Cheng (16 shared papers)Weili Zhao (16 shared papers)Hongmei Yi (11 shared papers)
- Journals
- Signal Transduction and Targeted Therapy (3 papers)Insects (3 papers)Frontiers in Oncology (3 papers)Scientific Reports (2 papers)Frontiers in Immunology (2 papers)
- Partner nations
- ChinaFranceUnited States
In The Last Decade
Di Fu
71 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Biochemistry 223
- Pathology and Forensic Medicine 314
- Endocrine and Autonomic Systems 80
- Cancer Research 174
- Oncology 303
Countries citing papers authored by Di Fu
This map shows the geographic impact of Di Fu'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 Di Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Fu more than expected).
Fields of papers citing papers by Di Fu
This network shows the impact of papers produced by Di Fu. 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 Di Fu. The network helps show where Di Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Di Fu, 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 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 269 | |
| 2 | Butyrate-producing Eubacterium rectale suppresses lymphomagenesis by alleviating the TNF-induced TLR4/MyD88/NF-κB axis Hit paper breakdown → | 2022 | 119 |
| 3 | 2019 | 81 | |
| 4 | 2018 | 63 | |
| 5 | 2020 | 55 | |
| 6 | 2023 | 47 | |
| 7 | 2023 | 46 | |
| 8 | 2023 | 44 | |
| 9 | 2022 | 38 | |
| 10 | 2022 | 38 | |
| 11 | 2020 | 36 | |
| 12 | 2006 | 33 | |
| 13 | 2017 | 27 | |
| 14 | 2021 | 24 | |
| 15 | 2021 | 24 | |
| 16 | 2020 | 23 | |
| 17 | 2022 | 22 | |
| 18 | 2004 | 21 | |
| 19 | 2010 | 19 | |
| 20 | 2013 | 17 |
About Di Fu
Di Fu is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Oncology, Immunology and Pulmonary and Respiratory Medicine, having authored 76 papers that have together received 1.3k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (20 papers), CAR-T cell therapy research (11 papers), Immune Cell Function and Interaction (8 papers), Pain Mechanisms and Treatments (5 papers), Viral-associated cancers and disorders (5 papers), Cancer-related gene regulation (5 papers), Pharmaceutical studies and practices (4 papers) and Insect Resistance and Genetics (4 papers). The work is most often cited by research in Biochemistry (223 citations), Pathology and Forensic Medicine (314 citations), Endocrine and Autonomic Systems (80 citations), Cancer Research (174 citations) and Oncology (303 citations). Di Fu has collaborated with scholars based in China, France and United States. Frequent co-authors include Shabbir Moochhala, Philip K. Moore, Madhav Bhatia, Li Wang, Pengpeng Xu, Shu Cheng, Weili Zhao, Hongmei Yi, Weili Zhao and Yan Zhao. Their work appears in journals such as Signal Transduction and Targeted Therapy, Insects, Frontiers in Oncology, Scientific Reports and Frontiers in Immunology.
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.