Shane Cheung
Impact in
- Biophysics top 10%
- Spectroscopy top 10%
- Molecular Sensors and Ion Detection
Papers in
-
- Nanoplatforms for cancer theranostics 7
- Co-authors
- Donal F. O’Shea (11 shared papers)Dan Wu (8 shared papers)Marco Grossi (2 shared papers)Jeremy C. Simpson (2 shared papers)Dimitri Scholz (2 shared papers)Emer Conroy (1 shared paper)Marta Terrile (1 shared paper)William M. Gallagher (1 shared paper)
- Journals
- The Journal of Immunology (2 papers)Nature Communications (2 papers)eLife (2 papers)Chemical Communications (2 papers)European Journal of Organic Chemistry (1 paper)
- Partner nations
- IrelandAustraliaUnited States
In The Last Decade
Shane Cheung
17 papers receiving 513 citations
Peers
Comparison fields: 5 of 81
- Biophysics 42
- Spectroscopy 102
- Materials Chemistry 251
- Biomedical Engineering 192
- Organic Chemistry 95
Countries citing papers authored by Shane Cheung
This map shows the geographic impact of Shane Cheung'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 Shane Cheung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shane Cheung more than expected).
Fields of papers citing papers by Shane Cheung
This network shows the impact of papers produced by Shane Cheung. 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 Shane Cheung. The network helps show where Shane Cheung may publish in the future.
Co-authors
The 25 scholars most cited alongside Shane Cheung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 173 | |
| 2 | 2014 | 59 | |
| 3 | 2017 | 52 | |
| 4 | 2015 | 38 | |
| 5 | 2019 | 34 | |
| 6 | 2021 | 33 | |
| 7 | 2018 | 31 | |
| 8 | 2014 | 25 | |
| 9 | 2018 | 20 | |
| 10 | 2018 | 18 | |
| 11 | 2018 | 12 | |
| 12 | 2018 | 7 | |
| 13 | 2016 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2022 | 4 | |
| 16 | 2023 | 2 | |
| 17 | 2019 | 2 |
About Shane Cheung
Shane Cheung is a scholar working on Biomedical Engineering, Molecular Biology, Organic Chemistry, Materials Chemistry and Cellular and Molecular Neuroscience, having authored 17 papers that have together received 519 indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (7 papers), Luminescence and Fluorescent Materials (4 papers), Click Chemistry and Applications (4 papers), Molecular Sensors and Ion Detection (2 papers), Advanced Fluorescence Microscopy Techniques (2 papers), Neurobiology and Insect Physiology Research (2 papers), Carbon and Quantum Dots Applications (2 papers) and Immune Response and Inflammation (2 papers). The work is most often cited by research in Biophysics (42 citations), Spectroscopy (102 citations), Materials Chemistry (251 citations), Biomedical Engineering (192 citations) and Organic Chemistry (95 citations). Shane Cheung has collaborated with scholars based in Ireland, Australia and United States. Frequent co-authors include Donal F. O’Shea, Dan Wu, Marco Grossi, Jeremy C. Simpson, Dimitri Scholz, Emer Conroy, Marta Terrile, William M. Gallagher, Zhilong Chen and Luís Echegoyen. Their work appears in journals such as The Journal of Immunology, Nature Communications, eLife, Chemical Communications and European Journal of Organic Chemistry.
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.