Haiyin Yang
About
In The Last Decade
Haiyin Yang
10 papers receiving 258 citations
Peers
Comparison fields: 5 of 72
- Molecular Biology 154
- Biomedical Engineering 60
- Immunology 47
- Infectious Diseases 42
- Biomaterials 27
Countries citing papers authored by Haiyin Yang
This map shows the geographic impact of Haiyin Yang'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 Haiyin Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haiyin Yang more than expected).
Fields of papers citing papers by Haiyin Yang
This network shows the impact of papers produced by Haiyin Yang. 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 Haiyin Yang. The network helps show where Haiyin Yang may publish in the future.
Co-authorship network of co-authors of Haiyin Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Haiyin Yang. A scholar is included among the top collaborators of Haiyin Yang 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 Haiyin Yang. Haiyin Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 18 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 18 | |
| 6 | 23 | |
| 7 | 37 | |
| 8 | 48 | |
| 9 | 15 | |
| 10 | 81 | |
| 11 | 21 | |
| 12 | 1 |
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.