Minghui Wang
- Molecular Biology top 10%
- Electrical and Electronic Engineering top 10%
- Renewable Energy, Sustainability and the Environment top 5%
- Materials Chemistry
- Electronic, Optical and Magnetic Materials top 10%
- Co-authors
- Lei WangAo LiBin YuZhenyu XiaoYu LiuZuochao WangYuxiang BaoXueke Wu
- Topics
- Machine Learning in Bioinformatics (36 papers)Advanced battery technologies research (15 papers)Genomics and Phylogenetic Studies (14 papers)
- Cited by
- Renewable Energy, Sustainability and the EnvironmentElectronic, Optical and Magnetic MaterialsCatalysis
- Partner nations
- ChinaUnited StatesSouth Africa
In The Last Decade
Minghui Wang
66 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 120
- Molecular Biology 839
- Electrical and Electronic Engineering 632
- Renewable Energy, Sustainability and the Environment 589
- Materials Chemistry 338
- Electronic, Optical and Magnetic Materials 316
Countries citing papers authored by Minghui Wang
This map shows the geographic impact of Minghui 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 Minghui Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghui Wang more than expected).
Fields of papers citing papers by Minghui Wang
This network shows the impact of papers produced by Minghui 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 Minghui Wang. The network helps show where Minghui Wang may publish in the future.
Co-authorship network of co-authors of Minghui Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Minghui Wang. A scholar is included among the top collaborators of Minghui 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 Minghui Wang. Minghui 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 | 1 | |
| 2 | 8 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 23 | |
| 6 | 11 | |
| 7 | 17 | |
| 8 | 12 | |
| 9 | 2 | |
| 10 | 7 | |
| 11 | 251 | |
| 12 | 24 | |
| 13 | 22 | |
| 14 | 49 | |
| 15 | 54 | |
| 16 | 44 | |
| 17 | 67 | |
| 18 | 3 | |
| 19 | 48 | |
| 20 | 37 |
About Minghui Wang
Minghui Wang is a scholar working on Renewable Energy, Sustainability and the Environment, Computational Theory and Mathematics and Molecular Biology, having authored 72 papers that have together received 2.0k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (36 papers), Advanced battery technologies research (15 papers) and Genomics and Phylogenetic Studies (14 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (589 citations), Electronic, Optical and Magnetic Materials (316 citations) and Catalysis (94 citations). Minghui Wang has collaborated with scholars based in China, United States and South Africa. Frequent co-authors include Lei Wang, Ao Li, Bin Yu, Zhenyu Xiao, Yu Liu, Zuochao Wang, Yuxiang Bao, Xueke Wu, Dan Zhang and Jianping Lai. Their work appears in journals such as Nature Communications, Bioinformatics and PLoS ONE.
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.