Feifei Tang
Impact in
- Hematology top 1%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
- Transplantation top 5%
Papers in
- Hematology 49
- Hematopoietic Stem Cell Transplantation 38
- Acute Myeloid Leukemia Research 28
- Oncology 19
- Polyomavirus and related diseases 9
- Co-authors
- Lan‐Ping Xu (52 shared papers)Xiao‐Jun Huang (52 shared papers)Xiaohui Zhang (46 shared papers)Yu Wang (42 shared papers)Yu‐Hong Chen (40 shared papers)Fei Lei (2 shared papers)Xiao‐Dong Mo (35 shared papers)Chen‐Hua Yan (33 shared papers)
- Journals
- Blood (7 papers)Bone Marrow Transplantation (7 papers)Biology of Blood and Marrow Transplantation (6 papers)British Journal of Haematology (4 papers)Cancers (3 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Feifei Tang
81 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 106
- Hematology 597
- Transplantation 43
- Immunology 192
- Genetics 81
- Public Health, Environmental and Occupational Health 168
Countries citing papers authored by Feifei Tang
This map shows the geographic impact of Feifei Tang'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 Feifei Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feifei Tang more than expected).
Fields of papers citing papers by Feifei Tang
This network shows the impact of papers produced by Feifei Tang. 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 Feifei Tang. The network helps show where Feifei Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Feifei Tang, 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 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 117 | |
| 2 | 2017 | 115 | |
| 3 | 2016 | 85 | |
| 4 | 2021 | 65 | |
| 5 | 2020 | 51 | |
| 6 | 2019 | 41 | |
| 7 | 2022 | 38 | |
| 8 | 2023 | 36 | |
| 9 | 2020 | 34 | |
| 10 | 2019 | 30 | |
| 11 | 2018 | 27 | |
| 12 | 2018 | 26 | |
| 13 | 2021 | 25 | |
| 14 | 2018 | 22 | |
| 15 | 2022 | 20 | |
| 16 | 2019 | 19 | |
| 17 | 2020 | 17 | |
| 18 | 2020 | 14 | |
| 19 | 2018 | 13 | |
| 20 | 2018 | 12 |
About Feifei Tang
Feifei Tang is a scholar working on Hematology, Oncology, Immunology, Public Health, Environmental and Occupational Health and Molecular Biology, having authored 87 papers that have together received 1.0k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (38 papers), Acute Myeloid Leukemia Research (28 papers), Acute Lymphoblastic Leukemia research (10 papers), Polyomavirus and related diseases (9 papers), Immune Cell Function and Interaction (8 papers), Renal Transplantation Outcomes and Treatments (7 papers), Remote Sensing and LiDAR Applications (6 papers) and T-cell and B-cell Immunology (6 papers). The work is most often cited by research in Hematology (597 citations), Transplantation (43 citations), Immunology (192 citations), Genetics (81 citations) and Public Health, Environmental and Occupational Health (168 citations). Feifei Tang has collaborated with scholars based in China and United States. Frequent co-authors include Lan‐Ping Xu, Xiao‐Jun Huang, Xiaohui Zhang, Yu Wang, Yu‐Hong Chen, Fei Lei, Xiao‐Dong Mo, Chen‐Hua Yan, Yuqian Sun and Kai‐Yan Liu. Their work appears in journals such as Blood, Bone Marrow Transplantation, Biology of Blood and Marrow Transplantation, British Journal of Haematology and Cancers.
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.