Wei Wu
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Cancer Research top 10%
- Cancer, Lipids, and Metabolism
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- RNA modifications and cancer 4
- Epigenetics and DNA Methylation 3
- Oncology 17
- Co-authors
- Yuqing Jin (4 shared papers)Boni Ding (4 shared papers)Liyuan Qian (3 shared papers)Yehuan Sun (2 shared papers)Guangbo Qu (2 shared papers)Xue Tang (2 shared papers)Xu Li (1 shared paper)Zuoliang Qi (2 shared papers)
- Journals
- Medical Physics (2 papers)PLoS ONE (2 papers)Oncotarget (2 papers)OncoTargets and Therapy (2 papers)Lupus (2 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Wei Wu
121 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 140
- Health Informatics 75
- Cancer Research 213
- Oncology 228
- Pathology and Forensic Medicine 141
- Molecular Biology 539
Countries citing papers authored by Wei Wu
This map shows the geographic impact of Wei Wu'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 Wei Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Wu more than expected).
Fields of papers citing papers by Wei Wu
This network shows the impact of papers produced by Wei Wu. 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 Wei Wu. The network helps show where Wei Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Wu, 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 129 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 137 | |
| 2 | 2014 | 111 | |
| 3 | 2015 | 94 | |
| 4 | 2016 | 81 | |
| 5 | 2021 | 79 | |
| 6 | 2017 | 64 | |
| 7 | 2011 | 57 | |
| 8 | 2019 | 51 | |
| 9 | Prognostic significance of CXCL12, CXCR4, and CXCR7 in patients with breast cancer. | 2015 | 44 |
| 10 | 2021 | 43 | |
| 11 | 2018 | 41 | |
| 12 | 2014 | 41 | |
| 13 | 2020 | 36 | |
| 14 | 2024 | 35 | |
| 15 | 2019 | 31 | |
| 16 | 2008 | 23 | |
| 17 | 2019 | 22 | |
| 18 | 2008 | 22 | |
| 19 | 2020 | 21 | |
| 20 | 2016 | 19 |
About Wei Wu
Wei Wu is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Surgery and Pathology and Forensic Medicine, having authored 129 papers that have together received 1.7k indexed citations. Recurring topics across this work include Gastric Cancer Management and Outcomes (4 papers), Lung Cancer Diagnosis and Treatment (4 papers), RNA modifications and cancer (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Tuberculosis Research and Epidemiology (4 papers), Neuroblastoma Research and Treatments (3 papers), Epigenetics and DNA Methylation (3 papers) and Acute Lymphoblastic Leukemia research (3 papers). The work is most often cited by research in Health Informatics (75 citations), Cancer Research (213 citations), Oncology (228 citations), Pathology and Forensic Medicine (141 citations) and Molecular Biology (539 citations). Wei Wu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Yuqing Jin, Boni Ding, Liyuan Qian, Yehuan Sun, Guangbo Qu, Xue Tang, Xu Li, Zuoliang Qi, Lingling Wang and Kaifeng Gan. Their work appears in journals such as Medical Physics, PLoS ONE, Oncotarget, OncoTargets and Therapy and Lupus.
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.