Sitong Wu
Impact in
-
- Advanced Neural Network Applications
-
- Nanoplatforms for cancer theranostics
- Photoacoustic and Ultrasonic Imaging
Papers in
-
- Natural product bioactivities and synthesis 7
- Synthesis and bioactivity of alkaloids 2
- Co-authors
- Guodong Guo (2 shared papers)Tianyi Wu (1 shared paper)Jianwen Luo (1 shared paper)Mingming Gong (1 shared paper)Shuo Li (1 shared paper)Zhi Liu (1 shared paper)Heye Zhang (1 shared paper)Zhifan Gao (1 shared paper)
- Journals
- Phytochemistry (4 papers)Dalton Transactions (2 papers)Journal of Natural Products (2 papers)Food Research International (1 paper)International Journal of Biological Macromolecules (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Sitong Wu
38 papers receiving 344 citations
Peers
Comparison fields: 5 of 99
- Computer Vision and Pattern Recognition 60
- Biomedical Engineering 97
- Radiology, Nuclear Medicine and Imaging 49
- Biotechnology 16
- Materials Chemistry 84
Countries citing papers authored by Sitong Wu
This map shows the geographic impact of Sitong 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 Sitong Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sitong Wu more than expected).
Fields of papers citing papers by Sitong Wu
This network shows the impact of papers produced by Sitong 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 Sitong Wu. The network helps show where Sitong Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Sitong 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 55 | |
| 2 | 2022 | 43 | |
| 3 | 2023 | 37 | |
| 4 | 2022 | 28 | |
| 5 | 2018 | 16 | |
| 6 | 2021 | 15 | |
| 7 | 2023 | 14 | |
| 8 | 2022 | 13 | |
| 9 | 2018 | 12 | |
| 10 | 2024 | 10 | |
| 11 | 2018 | 10 | |
| 12 | 2022 | 9 | |
| 13 | 2024 | 8 | |
| 14 | 2024 | 7 | |
| 15 | 2024 | 7 | |
| 16 | 2020 | 7 | |
| 17 | 2022 | 7 | |
| 18 | 2017 | 6 | |
| 19 | 2018 | 6 | |
| 20 | 2025 | 5 |
About Sitong Wu
Sitong Wu is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Pharmacology and Biomedical Engineering, having authored 42 papers that have together received 351 indexed citations. Recurring topics across this work include Natural product bioactivities and synthesis (7 papers), Nanoplatforms for cancer theranostics (3 papers), Microbial Natural Products and Biosynthesis (3 papers), Advanced Neural Network Applications (3 papers), Phytochemistry and Bioactive Compounds (3 papers), Synthesis and bioactivity of alkaloids (2 papers), Phytochemistry and Biological Activities (2 papers) and Climate Change Policy and Economics (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (60 citations), Biomedical Engineering (97 citations), Radiology, Nuclear Medicine and Imaging (49 citations), Biotechnology (16 citations) and Materials Chemistry (84 citations). Sitong Wu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Guodong Guo, Tianyi Wu, Jianwen Luo, Mingming Gong, Shuo Li, Zhi Liu, Heye Zhang, Zhifan Gao, Dayong Jin and Jiajia Zhou. Their work appears in journals such as Phytochemistry, Dalton Transactions, Journal of Natural Products, Food Research International and International Journal of Biological Macromolecules.
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.