Wenxuan Wang
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Artificial Intelligence top 10%
- Organic Chemistry
- Pharmacology
- Co-authors
- Xiangxiang ZengChengkun WuAiping LyuYouchao DengTingjun HouNingning WangZhenhua WuJinfu Peng
- Topics
- Natural Language Processing Techniques (6 papers)Topic Modeling (5 papers)Adversarial Robustness in Machine Learning (4 papers)
- Journals
- Nucleic Acids ResearchIEEE Transactions on Pattern Analysis and Machine IntelligenceChemical Engineering Journal
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Wenxuan Wang
22 papers receiving 499 citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Molecular Biology 140
- Computational Theory and Mathematics 124
- Artificial Intelligence 100
- Organic Chemistry 81
- Pharmacology 38
Countries citing papers authored by Wenxuan Wang
This map shows the geographic impact of Wenxuan 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 Wenxuan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenxuan Wang more than expected).
Fields of papers citing papers by Wenxuan Wang
This network shows the impact of papers produced by Wenxuan 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 Wenxuan Wang. The network helps show where Wenxuan Wang may publish in the future.
Co-authorship network of co-authors of Wenxuan Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Wenxuan Wang. A scholar is included among the top collaborators of Wenxuan Wang 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 Wenxuan Wang. Wenxuan Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 7 | |
| 10 | 0 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision supportbreakdown → | 349 |
| 14 | 5 | |
| 15 | 7 | |
| 16 | 23 | |
| 17 | 14 | |
| 18 | 14 | |
| 19 | 10 | |
| 20 | 31 |
About Wenxuan Wang
Wenxuan Wang is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 26 papers that have together received 507 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers) and Adversarial Robustness in Machine Learning (4 papers). The work is most often cited by research in Computational Theory and Mathematics (124 citations), Health Informatics (10 citations) and Pharmacology (33 citations). Wenxuan Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Xiangxiang Zeng, Chengkun Wu, Aiping Lyu, Youchao Deng, Tingjun Hou, Ningning Wang, Zhenhua Wu, Jinfu Peng, Wentao Zhao and Li Fu. Their work appears in journals such as Nucleic Acids Research, IEEE Transactions on Pattern Analysis and Machine Intelligence and Chemical Engineering Journal.
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.