Massimo Cavallaro
Impact in
Papers in
- Epidemiology 10
- Substance Abuse Treatment and Outcomes 3
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- Single-cell and spatial transcriptomics 2
- RNA Research and Splicing 2
- Co-authors
- Vito Latora (1 shared paper)Domenico Asprone (1 shared paper)Gaetano Manfredi (1 shared paper)Vincenzo Nicosia (1 shared paper)Matt J. Keeling (5 shared papers)Rosangela Cocchia (4 shared papers)Raffaele Calabrò (4 shared papers)Maria Giovanna Russo (4 shared papers)
- Journals
- PLoS Computational Biology (2 papers)iScience (1 paper)Journal of Adolescent Health (1 paper)Nature Communications (1 paper)Genome biology (1 paper)
- Partner nations
- United KingdomItalyIreland
In The Last Decade
Massimo Cavallaro
26 papers receiving 534 citations
Peers
Comparison fields: 5 of 100
- Virology 50
- Neurology 87
- Health Informatics 8
- Applied Microbiology and Biotechnology 8
- Cardiology and Cardiovascular Medicine 72
Countries citing papers authored by Massimo Cavallaro
This map shows the geographic impact of Massimo Cavallaro'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 Massimo Cavallaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Cavallaro more than expected).
Fields of papers citing papers by Massimo Cavallaro
This network shows the impact of papers produced by Massimo Cavallaro. 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 Massimo Cavallaro. The network helps show where Massimo Cavallaro may publish in the future.
Co-authors
The 25 scholars most cited alongside Massimo Cavallaro, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 107 | |
| 2 | 2016 | 89 | |
| 3 | 2016 | 65 | |
| 4 | 1993 | 60 | |
| 5 | 2023 | 58 | |
| 6 | 2010 | 39 | |
| 7 | 2023 | 24 | |
| 8 | 2018 | 21 | |
| 9 | 2021 | 15 | |
| 10 | 2021 | 15 | |
| 11 | 2010 | 12 | |
| 12 | 2016 | 8 | |
| 13 | 2017 | 8 | |
| 14 | 2015 | 5 | |
| 15 | 2009 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 2025 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2022 | 1 |
About Massimo Cavallaro
Massimo Cavallaro is a scholar working on Epidemiology, Molecular Biology, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Neurology, having authored 28 papers that have together received 545 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (4 papers), Substance Abuse Treatment and Outcomes (3 papers), Advanced Thermodynamics and Statistical Mechanics (2 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Machine Learning in Healthcare (2 papers), Single-cell and spatial transcriptomics (2 papers), Cardiovascular and Diving-Related Complications (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Virology (50 citations), Neurology (87 citations), Health Informatics (8 citations), Applied Microbiology and Biotechnology (8 citations) and Cardiology and Cardiovascular Medicine (72 citations). Massimo Cavallaro has collaborated with scholars based in United Kingdom, Italy and Ireland. Frequent co-authors include Vito Latora, Domenico Asprone, Gaetano Manfredi, Vincenzo Nicosia, Matt J. Keeling, Rosangela Cocchia, Raffaele Calabrò, Maria Giovanna Russo, Marianna Conte and Lucia Riegler. Their work appears in journals such as PLoS Computational Biology, iScience, Journal of Adolescent Health, Nature Communications and Genome biology.
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.