Guido Uguzzoni
Impact in
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- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Machine Learning in Bioinformatics
- Microbial Metabolic Engineering and Bioproduction
Papers in
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- Protein Structure and Dynamics 5
- vaccines and immunoinformatics approaches 3
- Gene Regulatory Network Analysis 2
- Machine Learning in Bioinformatics 2
- Microbial Metabolic Engineering and Bioproduction 2
- Bioinformatics and Genomic Networks 2
- Genetics 3
- Evolution and Genetic Dynamics 2
- Co-authors
- Martin Weigt (3 shared papers)Andrea Pagnani (7 shared papers)Francesco Oteri (2 shared papers)Francesco Zamponi (1 shared paper)Alexander H. Schug (1 shared paper)Hendrik Szurmant (1 shared paper)Jorge Fernández-de-Cossio-Díaz (5 shared papers)Elena Agliari (3 shared papers)
In The Last Decade
Guido Uguzzoni
15 papers receiving 252 citations
Peers
Comparison fields: 5 of 63
- Molecular Biology 179
- Statistical and Nonlinear Physics 23
- Computational Mathematics 1
- Genetics 41
- Acoustics and Ultrasonics 1
Countries citing papers authored by Guido Uguzzoni
This map shows the geographic impact of Guido Uguzzoni'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 Guido Uguzzoni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guido Uguzzoni more than expected).
Fields of papers citing papers by Guido Uguzzoni
This network shows the impact of papers produced by Guido Uguzzoni. 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 Guido Uguzzoni. The network helps show where Guido Uguzzoni may publish in the future.
Co-authors
The 23 scholars most cited alongside Guido Uguzzoni, 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 | 2017 | 70 | |
| 2 | 2021 | 61 | |
| 3 | 2016 | 23 | |
| 4 | 2016 | 21 | |
| 5 | 2020 | 16 | |
| 6 | 2012 | 12 | |
| 7 | 2020 | 12 | |
| 8 | 2017 | 11 | |
| 9 | 2013 | 10 | |
| 10 | 2012 | 7 | |
| 11 | 2021 | 5 | |
| 12 | 2024 | 3 | |
| 13 | 2024 | 3 | |
| 14 | 2024 | 1 | |
| 15 | 2012 | 1 |
About Guido Uguzzoni
Guido Uguzzoni is a scholar working on Molecular Biology, Genetics, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging and Modeling and Simulation, having authored 15 papers that have together received 256 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), vaccines and immunoinformatics approaches (3 papers), Gene Regulatory Network Analysis (2 papers), Machine Learning in Bioinformatics (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Evolution and Genetic Dynamics (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Molecular Biology (179 citations), Statistical and Nonlinear Physics (23 citations), Computational Mathematics (1 citation), Genetics (41 citations) and Acoustics and Ultrasonics (1 citation). Guido Uguzzoni has collaborated with scholars based in Italy, France and Cuba. Frequent co-authors include Martin Weigt, Andrea Pagnani, Francesco Oteri, Francesco Zamponi, Alexander H. Schug, Hendrik Szurmant, Jorge Fernández-de-Cossio-Díaz, Elena Agliari, Paolo Marcatili and Raffaella Burioni. Their work appears in journals such as PLoS Computational Biology, Bioinformatics, International Journal of Molecular Sciences, Scientific Reports 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.