Weida Wang
Impact in
- Oncology top 10%
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
- Hematology top 5%
- Acute Myeloid Leukemia Research
- Multiple Myeloma Research and Treatments
Papers in
- Hematology 22
- Multiple Myeloma Research and Treatments 15
- Acute Myeloid Leukemia Research 6
- Oncology 10
- Co-authors
- Yue Lu (9 shared papers)Hua Wang (5 shared papers)Xiaoguang Chen (10 shared papers)Zhongjun Xia (9 shared papers)Sen Zhang (7 shared papers)Yang Liang (16 shared papers)Liang Wang (3 shared papers)Jing Zhang (1 shared paper)
- Journals
- Leukemia (5 papers)Blood (4 papers)OncoTargets and Therapy (3 papers)Annals of Hematology (3 papers)BMC Cancer (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Weida Wang
71 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 102
- Oncology 306
- Hematology 176
- Cancer Research 155
- Genetics 87
- Infectious Diseases 118
Countries citing papers authored by Weida Wang
This map shows the geographic impact of Weida Wang'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 Weida Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weida Wang more than expected).
Fields of papers citing papers by Weida Wang
This network shows the impact of papers produced by Weida Wang. 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 Weida Wang. The network helps show where Weida Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Weida Wang, 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 80 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 174 | |
| 2 | 2020 | 129 | |
| 3 | 2020 | 80 | |
| 4 | 2018 | 67 | |
| 5 | 2018 | 60 | |
| 6 | 2021 | 49 | |
| 7 | 2023 | 47 | |
| 8 | 2014 | 44 | |
| 9 | 2021 | 37 | |
| 10 | 2020 | 35 | |
| 11 | 2021 | 33 | |
| 12 | 2021 | 32 | |
| 13 | 2020 | 31 | |
| 14 | 2017 | 29 | |
| 15 | 2020 | 29 | |
| 16 | 2022 | 26 | |
| 17 | 2022 | 25 | |
| 18 | 2017 | 23 | |
| 19 | 2020 | 22 | |
| 20 | 2018 | 21 |
About Weida Wang
Weida Wang is a scholar working on Hematology, Oncology, Pathology and Forensic Medicine, Cancer Research and Genetics, having authored 80 papers that have together received 1.4k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (15 papers), Acute Myeloid Leukemia Research (6 papers), Lymphoma Diagnosis and Treatment (4 papers), Natural Compounds in Disease Treatment (3 papers), Immune cells in cancer (3 papers), Renal Diseases and Glomerulopathies (3 papers), Virus-based gene therapy research (3 papers) and COVID-19 Clinical Research Studies (3 papers). The work is most often cited by research in Oncology (306 citations), Hematology (176 citations), Cancer Research (155 citations), Genetics (87 citations) and Infectious Diseases (118 citations). Weida Wang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yue Lu, Hua Wang, Xiaoguang Chen, Zhongjun Xia, Sen Zhang, Yang Liang, Liang Wang, Jing Zhang, Sheng Hu and Qian Yu. Their work appears in journals such as Leukemia, Blood, OncoTargets and Therapy, Annals of Hematology and BMC Cancer.
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.