Song Wu
- Pathology and Forensic Medicine top 10%
- Cardiology and Cardiovascular Medicine top 10%
- Molecular Biology
- Emergency Medicine top 10%
- Complementary and alternative medicine top 5%
- Co-authors
- Tak‐Ming WongJianming PeiXiao-Chun YuGuanying WangTak Ming WongGennadi M. KravtsovJing LiuJia Li
- Topics
- Acupuncture Treatment Research Studies (18 papers)Healthcare and Venom Research (11 papers)Traditional Chinese Medicine Studies (10 papers)
- Cited by
- Developmental NeuroscienceComplementary and alternative medicinePathology and Forensic Medicine
In The Last Decade
Song Wu
34 papers receiving 434 citations
Peers
Comparison fields: 5 of 72
- Pathology and Forensic Medicine 170
- Cardiology and Cardiovascular Medicine 144
- Molecular Biology 119
- Emergency Medicine 87
- Complementary and alternative medicine 81
Countries citing papers authored by Song Wu
This map shows the geographic impact of Song 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 Song Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Wu more than expected).
Fields of papers citing papers by Song Wu
This network shows the impact of papers produced by Song 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 Song Wu. The network helps show where Song Wu may publish in the future.
Co-authorship network of co-authors of Song Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Song Wu. A scholar is included among the top collaborators of Song Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Song Wu. Song Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 29 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 6 | |
| 8 | 3 | |
| 9 | [Effects of electroacupuncture at different acupoints on apoptosis and the expression of miRNAs in myocardial cells in rats model of myocardial ischemia]. | 2 |
| 10 | [Effects of electroacupuncture with branch-foundation acupoint combination on the pituitary-target gland axis in aging rats with yang deficiency]. | 3 |
| 11 | [Effects of electroacupuncture at "Neiguan" (PC 6) on p38 MAPK signaling pathway in rats with cardiac hypertrophy]. | 5 |
| 12 | 4 | |
| 13 | 1 | |
| 14 | 56 | |
| 15 | 21 | |
| 16 | 43 | |
| 17 | 6 | |
| 18 | 8 | |
| 19 | 8 | |
| 20 | 10 |
About Song Wu
Song Wu is a scholar working on Complementary and alternative medicine, Developmental Neuroscience and Pharmacology, having authored 35 papers that have together received 441 indexed citations. Recurring topics across this work include Acupuncture Treatment Research Studies (18 papers), Healthcare and Venom Research (11 papers) and Traditional Chinese Medicine Studies (10 papers). The work is most often cited by research in Developmental Neuroscience (59 citations), Complementary and alternative medicine (81 citations) and Pathology and Forensic Medicine (170 citations). Song Wu has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Tak‐Ming Wong, Jianming Pei, Xiao-Chun Yu, Guanying Wang, Tak Ming Wong, Gennadi M. Kravtsov, Jing Liu, Jia Li, Feng-Xia Liang and Jing‐Jun Zhou. Their work appears in journals such as British Journal of Pharmacology, American Journal of Physiology-Heart and Circulatory Physiology and American Journal of Physiology-Cell Physiology.
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.