Fabio Zuccotto
- Organic Chemistry top 5%
- Synthesis and Biological Evaluation 3
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- Computational Drug Discovery Methods 8
- Infectious Diseases top 10%
- Tuberculosis Research and Epidemiology 2
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- Biochemical and Molecular Research 6
- Protein Structure and Dynamics 5
- Glycosylation and Glycoproteins Research 3
- Epidemiology top 10%
- Trypanosoma species research and implications 9
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- Research on Leishmaniasis Studies 3
- Co-authors
- Elena CasaleMauro AngioliniElena ArdiniIan H. GilbertAnna BernardiReto BrunLuis M. Ruiz‐PérezDolores González‐Pacanowska
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Journal of the American Chemical Society (1 paper)PLoS ONE (1 paper)
- Partner nations
- United KingdomSpainItaly
In The Last Decade
Fabio Zuccotto
23 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 87
- Organic Chemistry 361
- Computational Theory and Mathematics 153
- Infectious Diseases 165
- Molecular Biology 591
- Epidemiology 275
Countries citing papers authored by Fabio Zuccotto
This map shows the geographic impact of Fabio Zuccotto'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 Fabio Zuccotto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Zuccotto more than expected).
Fields of papers citing papers by Fabio Zuccotto
This network shows the impact of papers produced by Fabio Zuccotto. 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 Fabio Zuccotto. The network helps show where Fabio Zuccotto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabio Zuccotto, 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 | 2024 | 5 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 12 | |
| 4 | 2021 | 16 | |
| 5 | 2021 | 12 | |
| 6 | 2020 | 12 | |
| 7 | 2019 | 0 | |
| 8 | 2019 | 4 | |
| 9 | 2018 | 14 | |
| 10 | 2018 | 29 | |
| 11 | 2018 | 14 | |
| 12 | 2018 | 88 | |
| 13 | 2014 | 34 | |
| 14 | 2010 | 18 | |
| 15 | 2009 | 397 | |
| 16 | 2003 | 48 | |
| 17 | 2003 | 18 | |
| 18 | 2001 | 55 | |
| 19 | 1999 | 24 | |
| 20 | 1998 | 57 |
About Fabio Zuccotto
Fabio Zuccotto is a scholar working on Computational Theory and Mathematics, Endocrinology and Molecular Biology, having authored 25 papers that have together received 1.1k indexed citations. Recurring topics across this work include Trypanosoma species research and implications (9 papers), Computational Drug Discovery Methods (8 papers), Biochemical and Molecular Research (6 papers), Protein Structure and Dynamics (5 papers), Glycosylation and Glycoproteins Research (3 papers), Research on Leishmaniasis Studies (3 papers), Synthesis and Biological Evaluation (3 papers) and Tuberculosis Research and Epidemiology (2 papers). The work is most often cited by research in Organic Chemistry (361 citations), Computational Theory and Mathematics (153 citations) and Infectious Diseases (165 citations). Fabio Zuccotto has collaborated with scholars based in United Kingdom, Spain and Italy. Frequent co-authors include Elena Casale, Mauro Angiolini, Elena Ardini, Ian H. Gilbert, Anna Bernardi, Reto Brun, Luis M. Ruiz‐Pérez, Dolores González‐Pacanowska, Paul G. Wyatt and David Horn. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and PLoS ONE.
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.