Weihao Tang
Impact in
-
- Computational Drug Discovery Methods
- Pollution top 10%
- Pharmaceutical and Antibiotic Environmental Impacts
Papers in
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- Metabolomics and Mass Spectrometry Studies 3
-
- Computational Drug Discovery Methods 7
- Co-authors
- Jingwen Chen (19 shared papers)Zhongyu Wang (8 shared papers)Huixiao Hong (5 shared papers)Hong‐Bin Xie (6 shared papers)Yiling Cao (2 shared papers)Deming Xia (4 shared papers)Wanxin Tang (1 shared paper)Tong Xu (4 shared papers)
- Journals
- Chemosphere (5 papers)Environmental Science & Technology (4 papers)Journal of Environmental Sciences (2 papers)BioMetals (1 paper)Nanomaterials (1 paper)
- Partner nations
- ChinaUnited StatesDenmark
In The Last Decade
Weihao Tang
30 papers receiving 642 citations
Peers
Comparison fields: 5 of 111
- Computational Theory and Mathematics 136
- Pollution 91
- Industrial and Manufacturing Engineering 62
- Health, Toxicology and Mutagenesis 92
- Environmental Chemistry 46
Countries citing papers authored by Weihao Tang
This map shows the geographic impact of Weihao Tang'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 Weihao Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weihao Tang more than expected).
Fields of papers citing papers by Weihao Tang
This network shows the impact of papers produced by Weihao Tang. 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 Weihao Tang. The network helps show where Weihao Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Weihao Tang, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 70 | |
| 2 | 2019 | 65 | |
| 3 | 2019 | 64 | |
| 4 | 2020 | 54 | |
| 5 | 2018 | 43 | |
| 6 | 2021 | 40 | |
| 7 | 2022 | 31 | |
| 8 | 2024 | 27 | |
| 9 | 2023 | 26 | |
| 10 | 2020 | 26 | |
| 11 | 2023 | 21 | |
| 12 | 2021 | 20 | |
| 13 | 2023 | 20 | |
| 14 | 2020 | 18 | |
| 15 | 2023 | 16 | |
| 16 | 2021 | 16 | |
| 17 | 2019 | 15 | |
| 18 | 2019 | 14 | |
| 19 | 2020 | 11 | |
| 20 | 2023 | 10 |
About Weihao Tang
Weihao Tang is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Health, Toxicology and Mutagenesis and Biomedical Engineering, having authored 33 papers that have together received 648 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Chemistry and Chemical Engineering (4 papers), Atmospheric chemistry and aerosols (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Nanoparticles: synthesis and applications (3 papers), Effects and risks of endocrine disrupting chemicals (3 papers), Advanced Chemical Sensor Technologies (3 papers) and Renal cell carcinoma treatment (2 papers). The work is most often cited by research in Computational Theory and Mathematics (136 citations), Pollution (91 citations), Industrial and Manufacturing Engineering (62 citations), Health, Toxicology and Mutagenesis (92 citations) and Environmental Chemistry (46 citations). Weihao Tang has collaborated with scholars based in China, United States and Denmark. Frequent co-authors include Jingwen Chen, Zhongyu Wang, Huixiao Hong, Hong‐Bin Xie, Yiling Cao, Deming Xia, Wanxin Tang, Tong Xu, Xuehua Li and Qing Zhao. Their work appears in journals such as Chemosphere, Environmental Science & Technology, Journal of Environmental Sciences, BioMetals and Nanomaterials.
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.