Matthew P. Cheng
- Infectious Diseases top 1%
- Epidemiology top 5%
- Molecular Biology
- Oncology top 10%
- Clinical Biochemistry top 2%
- Co-authors
- Cédric P. YansouniTodd C. LeeJesse PapenburgCaroline QuachGuillaume Butler‐LaporteSanjat KanjilalMichaël DesjardinsMichael Libman
- Topics
- SARS-CoV-2 and COVID-19 Research (24 papers)COVID-19 Clinical Research Studies (18 papers)Bacterial Identification and Susceptibility Testing (16 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Matthew P. Cheng
104 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Infectious Diseases 1.4k
- Epidemiology 826
- Molecular Biology 388
- Oncology 252
- Clinical Biochemistry 248
Countries citing papers authored by Matthew P. Cheng
This map shows the geographic impact of Matthew P. Cheng'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 Matthew P. Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew P. Cheng more than expected).
Fields of papers citing papers by Matthew P. Cheng
This network shows the impact of papers produced by Matthew P. Cheng. 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 Matthew P. Cheng. The network helps show where Matthew P. Cheng may publish in the future.
Co-authorship network of co-authors of Matthew P. Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew P. Cheng. A scholar is included among the top collaborators of Matthew P. Cheng 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 Matthew P. Cheng. Matthew P. Cheng 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 | 0 | |
| 3 | 0 | |
| 4 | 16 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 11 | |
| 10 | 29 | |
| 11 | 13 | |
| 12 | 27 | |
| 13 | Phase 1 randomized trial of a plant-derived virus-like particle vaccine for COVID-19breakdown → | 214 |
| 14 | 9 | |
| 15 | 4 | |
| 16 | 0 | |
| 17 | 40 | |
| 18 | 91 | |
| 19 | 3 | |
| 20 | 10 |
About Matthew P. Cheng
Matthew P. Cheng is a scholar working on Infectious Diseases, Microbiology and Applied Microbiology and Biotechnology, having authored 113 papers that have together received 2.6k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (24 papers), COVID-19 Clinical Research Studies (18 papers) and Bacterial Identification and Susceptibility Testing (16 papers). The work is most often cited by research in Infectious Diseases (1.4k citations), Applied Microbiology and Biotechnology (91 citations) and Clinical Biochemistry (248 citations). Matthew P. Cheng has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Cédric P. Yansouni, Todd C. Lee, Jesse Papenburg, Caroline Quach, Guillaume Butler‐Laporte, Sanjat Kanjilal, Michaël Desjardins, Michael Libman, Sabine Dittrich and Emily G. McDonald. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Nature Communications.
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.