John M. Nicholls
- Infectious Diseases top 0.05%
- Epidemiology top 0.2%
- Molecular Biology top 2%
- Immunology top 0.5%
- Oncology top 1%
- Co-authors
- Malik PeirisLeo L. M. PoonYi GuanMichael C. W. ChanRenee W. Y. ChanKwok‐Yung YuenChung Yan CheungTK Ng
- Topics
- Influenza Virus Research Studies (79 papers)Respiratory viral infections research (59 papers)Viral-associated cancers and disorders (27 papers)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
John M. Nicholls
271 papers receiving 18.4k citations
Hit Papers
Peers
Comparison fields: 5 of 218
- Infectious Diseases 7.4k
- Epidemiology 5.7k
- Molecular Biology 3.5k
- Immunology 3.0k
- Oncology 2.6k
Countries citing papers authored by John M. Nicholls
This map shows the geographic impact of John M. Nicholls'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 John M. Nicholls with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John M. Nicholls more than expected).
Fields of papers citing papers by John M. Nicholls
This network shows the impact of papers produced by John M. Nicholls. 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 John M. Nicholls. The network helps show where John M. Nicholls may publish in the future.
Co-authorship network of co-authors of John M. Nicholls
This figure shows the co-authorship network connecting the top 25 collaborators of John M. Nicholls. A scholar is included among the top collaborators of John M. Nicholls 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 John M. Nicholls. John M. Nicholls is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 21 | |
| 3 | SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivobreakdown → | 496 |
| 4 | 25 | |
| 5 | 14 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 59 | |
| 9 | 3 | |
| 10 | 135 | |
| 11 | 53 | |
| 12 | 86 | |
| 13 | 70 | |
| 14 | Activity of the EBNA1 promoter associated with lytic replication (Fp) in Epstein-Barr virus associated disorders | 2 |
| 15 | 9 | |
| 16 | 154 | |
| 17 | 48 | |
| 18 | 6 | |
| 19 | Impact of zonal retrieval arrangements in the United Kingdom: the donor coordinator's perspective. | 1 |
| 20 | 30 |
About John M. Nicholls
John M. Nicholls is a scholar working on Otorhinolaryngology, Infectious Diseases and Epidemiology, having authored 277 papers that have together received 19.1k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (79 papers), Respiratory viral infections research (59 papers) and Viral-associated cancers and disorders (27 papers). The work is most often cited by research in Infectious Diseases (7.4k citations), Epidemiology (5.7k citations) and Modeling and Simulation (690 citations). John M. Nicholls has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Malik Peiris, Leo L. M. Poon, Yi Guan, Michael C. W. Chan, Renee W. Y. Chan, Kwok‐Yung Yuen, Chung Yan Cheung, TK Ng, W. Lim and Dnc Tsang. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and The Lancet.
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.