Angelo S. Mao
- Biomedical Engineering top 0.5%
- Molecular Biology top 5%
- Cell Biology top 1%
- Biomaterials top 1%
- Surgery top 5%
- Co-authors
- David MooneyPraveen AranyOmar A. AliSidi A. BencherifDmitry ShvartsmanJosé Rivera‐FelicianoNathaniel HuebschDavid A. Weitz
- Topics
- 3D Printing in Biomedical Research (12 papers)Cellular Mechanics and Interactions (6 papers)Innovative Microfluidic and Catalytic Techniques Innovation (4 papers)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Angelo S. Mao
26 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Biomedical Engineering 2.9k
- Molecular Biology 1.3k
- Cell Biology 1.1k
- Biomaterials 838
- Surgery 598
Countries citing papers authored by Angelo S. Mao
This map shows the geographic impact of Angelo S. 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 Angelo S. Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Angelo S. Mao more than expected).
Fields of papers citing papers by Angelo S. Mao
This network shows the impact of papers produced by Angelo S. 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 Angelo S. Mao. The network helps show where Angelo S. Mao may publish in the future.
Co-authorship network of co-authors of Angelo S. Mao
This figure shows the co-authorship network connecting the top 25 collaborators of Angelo S. Mao. A scholar is included among the top collaborators of Angelo S. 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 Angelo S. Mao. Angelo S. 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 | 15 | |
| 2 | Minimally instrumented SHERLOCK (miSHERLOCK) for CRISPR-based point-of-care diagnosis of SARS-CoV-2 and emerging variantsbreakdown → | 236 |
| 3 | 58 | |
| 4 | 3 | |
| 5 | 75 | |
| 6 | 96 | |
| 7 | 61 | |
| 8 | 150 | |
| 9 | 84 | |
| 10 | 61 | |
| 11 | 289 | |
| 12 | 99 | |
| 13 | 151 | |
| 14 | Cell volume change through water efflux impacts cell stiffness and stem cell fatebreakdown → | 366 |
| 15 | 34 | |
| 16 | 47 | |
| 17 | 229 | |
| 18 | 294 | |
| 19 | 4 | |
| 20 | Harnessing traction-mediated manipulation of the cell/matrix interface to control stem-cell fatebreakdown → | 1294 |
About Angelo S. Mao
Angelo S. Mao is a scholar working on Cell Biology, Biomedical Engineering and Genetics, having authored 26 papers that have together received 4.9k indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (12 papers), Cellular Mechanics and Interactions (6 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (4 papers). The work is most often cited by research in Molecular Medicine (423 citations), Biomedical Engineering (2.9k citations) and Cell Biology (1.1k citations). Angelo S. Mao has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include David Mooney, Praveen Arany, Omar A. Ali, Sidi A. Bencherif, Dmitry Shvartsman, José Rivera‐Feliciano, Nathaniel Huebsch, David A. Weitz, Jae‐Won Shin and Stefanie Utech. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences 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.