Francesco Trozzi
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Protein Structure and Dynamics 6
- Photosynthetic Processes and Mechanisms 3
- Machine Learning in Bioinformatics 1
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- Machine Learning in Materials Science 4
- Co-authors
- Peng Tao (10 shared papers)Xinlei Wang (1 shared paper)Brian D. Zoltowski (5 shared papers)Hao Tian (3 shared papers)Elfi Kraka (3 shared papers)Niraj Verma (3 shared papers)Eric C. Larson (2 shared papers)Xi Jiang (1 shared paper)
- Journals
- International Journal of Molecular Sciences (2 papers)Organic & Biomolecular Chemistry (2 papers)The Journal of Physical Chemistry B (2 papers)Israel Journal of Chemistry (1 paper)Frontiers in Molecular Biosciences (1 paper)
- Partner nations
- United StatesItaly
In The Last Decade
Francesco Trozzi
12 papers receiving 232 citations
Peers
Comparison fields: 5 of 76
- Computational Theory and Mathematics 111
- Health Informatics 6
- Molecular Biology 147
- Structural Biology 3
- Materials Chemistry 80
Countries citing papers authored by Francesco Trozzi
This map shows the geographic impact of Francesco Trozzi'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 Francesco Trozzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Trozzi more than expected).
Fields of papers citing papers by Francesco Trozzi
This network shows the impact of papers produced by Francesco Trozzi. 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 Francesco Trozzi. The network helps show where Francesco Trozzi may publish in the future.
Co-authors
The 22 scholars most cited alongside Francesco Trozzi, 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 | 2021 | 70 | |
| 2 | 2021 | 31 | |
| 3 | 2021 | 30 | |
| 4 | 2021 | 30 | |
| 5 | 2020 | 20 | |
| 6 | 2016 | 14 | |
| 7 | 2021 | 13 | |
| 8 | 2023 | 13 | |
| 9 | 2022 | 10 | |
| 10 | 2021 | 6 | |
| 11 | 2022 | 3 | |
| 12 | 2021 | 2 |
About Francesco Trozzi
Francesco Trozzi is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Infectious Diseases and Cellular and Molecular Neuroscience, having authored 12 papers that have together received 242 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (4 papers), Photosynthetic Processes and Mechanisms (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Light effects on plants (2 papers), Photoreceptor and optogenetics research (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Computational Theory and Mathematics (111 citations), Health Informatics (6 citations), Molecular Biology (147 citations), Structural Biology (3 citations) and Materials Chemistry (80 citations). Francesco Trozzi has collaborated with scholars based in United States and Italy. Frequent co-authors include Peng Tao, Xinlei Wang, Brian D. Zoltowski, Hao Tian, Elfi Kraka, Niraj Verma, Eric C. Larson, Xi Jiang, Sian Xiao and Zilin Song. Their work appears in journals such as International Journal of Molecular Sciences, Organic & Biomolecular Chemistry, The Journal of Physical Chemistry B, Israel Journal of Chemistry and Frontiers in Molecular Biosciences.
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.