Weida Wang
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- Hematology top 10%
- Multiple Myeloma Research and Treatments
Papers in
-
- Protein Degradation and Inhibitors 7
- RNA modifications and cancer 5
- Hematology 21
- Multiple Myeloma Research and Treatments 12
- Acute Myeloid Leukemia Research 6
- Co-authors
- Yue Lu (9 shared papers)Wenjian Liu (5 shared papers)Hua Wang (5 shared papers)Xiaoguang Chen (9 shared papers)Sen Zhang (7 shared papers)Liang Wang (3 shared papers)Liang Wang (6 shared papers)Yang Liang (11 shared papers)
- Journals
- Blood (6 papers)Leukemia (4 papers)OncoTargets and Therapy (3 papers)Pharmaceuticals (2 papers)BMC Cancer (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Weida Wang
73 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 111
- Cancer Research 183
- Hematology 118
- Oncology 196
- Genetics 62
- Infectious Diseases 103
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 | 2020 | 114 | |
| 2 | 2020 | 77 | |
| 3 | 2018 | 66 | |
| 4 | 2018 | 60 | |
| 5 | 2021 | 46 | |
| 6 | 2014 | 40 | |
| 7 | 2021 | 39 | |
| 8 | 2023 | 38 | |
| 9 | 2020 | 31 | |
| 10 | 2020 | 30 | |
| 11 | 2021 | 29 | |
| 12 | 2020 | 28 | |
| 13 | 2017 | 28 | |
| 14 | 2022 | 26 | |
| 15 | 2020 | 22 | |
| 16 | 2017 | 22 | |
| 17 | 2022 | 21 | |
| 18 | 2015 | 21 | |
| 19 | 2018 | 20 | |
| 20 | 2023 | 19 |
About Weida Wang
Weida Wang is a scholar working on Molecular Biology, Hematology, Oncology, Cancer Research and Pathology and Forensic Medicine, having authored 80 papers that have together received 1.1k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (12 papers), Protein Degradation and Inhibitors (7 papers), Cancer-related molecular mechanisms research (6 papers), Acute Myeloid Leukemia Research (6 papers), Lymphoma Diagnosis and Treatment (5 papers), RNA modifications and cancer (5 papers), Immune cells in cancer (4 papers) and Acute Lymphoblastic Leukemia research (4 papers). The work is most often cited by research in Cancer Research (183 citations), Hematology (118 citations), Oncology (196 citations), Genetics (62 citations) and Infectious Diseases (103 citations). Weida Wang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yue Lu, Wenjian Liu, Hua Wang, Xiaoguang Chen, Sen Zhang, Liang Wang, Liang Wang, Yang Liang, Zhongjun Xia and Lingling Shu. Their work appears in journals such as Blood, Leukemia, OncoTargets and Therapy, Pharmaceuticals 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.