Lorenzo Subissi
- Infectious Diseases top 1%
- Molecular Biology
- Animal Science and Zoology top 2%
- Computational Theory and Mathematics top 2%
- Epidemiology
- Co-authors
- Isabelle ImbertÉtienne DecrolyBruno CanardLaure GluaisMarion SevajolJessika C. Zevenhoven-DobbeClara C. PosthumaAlexander E. Gorbalenya
- Topics
- Viral Infections and Outbreaks Research (14 papers)SARS-CoV-2 and COVID-19 Research (12 papers)Viral gastroenteritis research and epidemiology (7 papers)
- Journals
- Proceedings of the National Academy of SciencesThe LancetThe Journal of Infectious Diseases
- Partner nations
- SwitzerlandBelgiumUnited Kingdom
In The Last Decade
Lorenzo Subissi
39 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Infectious Diseases 1.2k
- Molecular Biology 415
- Animal Science and Zoology 239
- Computational Theory and Mathematics 197
- Epidemiology 190
Countries citing papers authored by Lorenzo Subissi
This map shows the geographic impact of Lorenzo Subissi'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 Lorenzo Subissi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lorenzo Subissi more than expected).
Fields of papers citing papers by Lorenzo Subissi
This network shows the impact of papers produced by Lorenzo Subissi. 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 Lorenzo Subissi. The network helps show where Lorenzo Subissi may publish in the future.
Co-authorship network of co-authors of Lorenzo Subissi
This figure shows the co-authorship network connecting the top 25 collaborators of Lorenzo Subissi. A scholar is included among the top collaborators of Lorenzo Subissi 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 Lorenzo Subissi. Lorenzo Subissi 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 | 1 | |
| 4 | 69 | |
| 5 | 4 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 36 | |
| 11 | 14 | |
| 12 | 2 | |
| 13 | 27 | |
| 14 | 9 | |
| 15 | 10 | |
| 16 | 42 | |
| 17 | 15 | |
| 18 | 8 | |
| 19 | 135 | |
| 20 | 245 |
About Lorenzo Subissi
Lorenzo Subissi is a scholar working on Infectious Diseases, Modeling and Simulation and Emergency Medical Services, having authored 42 papers that have together received 1.7k indexed citations. Recurring topics across this work include Viral Infections and Outbreaks Research (14 papers), SARS-CoV-2 and COVID-19 Research (12 papers) and Viral gastroenteritis research and epidemiology (7 papers). The work is most often cited by research in Infectious Diseases (1.2k citations), Animal Science and Zoology (239 citations) and Virology (95 citations). Lorenzo Subissi has collaborated with scholars based in Switzerland, Belgium and United Kingdom. Frequent co-authors include Isabelle Imbert, Étienne Decroly, Bruno Canard, Laure Gluais, Marion Sevajol, Jessika C. Zevenhoven-Dobbe, Clara C. Posthuma, Alexander E. Gorbalenya, Eric J. Snijder and François Ferrón. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Lancet and The Journal of Infectious Diseases.
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.