Hai‐Quan Mao
- Molecular Biology top 1%
- Biomaterials top 0.05%
- Biomedical Engineering top 0.2%
- Surgery top 1%
- Cellular and Molecular Neuroscience top 0.5%
- Co-authors
- Kam W. LeongKrishnendu RoyShawn LimJun WangHongjun SongGregory T. ChristophersonShau Ku HuangJ. Thomas August
- Topics
- RNA Interference and Gene Delivery (82 papers)Electrospun Nanofibers in Biomedical Applications (53 papers)Advanced biosensing and bioanalysis techniques (46 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyAdvanced Materials
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Hai‐Quan Mao
234 papers receiving 14.6k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Molecular Biology 5.6k
- Biomaterials 5.4k
- Biomedical Engineering 4.3k
- Surgery 2.5k
- Cellular and Molecular Neuroscience 1.9k
Countries citing papers authored by Hai‐Quan Mao
This map shows the geographic impact of Hai‐Quan Mao'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 Hai‐Quan Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai‐Quan Mao more than expected).
Fields of papers citing papers by Hai‐Quan Mao
This network shows the impact of papers produced by Hai‐Quan Mao. 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 Hai‐Quan Mao. The network helps show where Hai‐Quan Mao may publish in the future.
Co-authorship network of co-authors of Hai‐Quan Mao
This figure shows the co-authorship network connecting the top 25 collaborators of Hai‐Quan Mao. A scholar is included among the top collaborators of Hai‐Quan Mao 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 Hai‐Quan Mao. Hai‐Quan Mao 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 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 7 | |
| 9 | 28 | |
| 10 | 18 | |
| 11 | 32 | |
| 12 | 51 | |
| 13 | 13 | |
| 14 | 56 | |
| 15 | 85 | |
| 16 | 38 | |
| 17 | 8 | |
| 18 | 71 | |
| 19 | 130 | |
| 20 | 16 |
About Hai‐Quan Mao
Hai‐Quan Mao is a scholar working on Biomaterials, Developmental Neuroscience and Pharmaceutical Science, having authored 243 papers that have together received 14.9k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (82 papers), Electrospun Nanofibers in Biomedical Applications (53 papers) and Advanced biosensing and bioanalysis techniques (46 papers). The work is most often cited by research in Biomaterials (5.4k citations), Pharmaceutical Science (1.3k citations) and Surfaces, Coatings and Films (782 citations). Hai‐Quan Mao has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Kam W. Leong, Krishnendu Roy, Shawn Lim, Jun Wang, Hongjun Song, Gregory T. Christopherson, Shau Ku Huang, J. Thomas August, José Luís Santos and John‐Michael Williford. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Advanced Materials.
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.