Candida Manelfi
Impact in
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- Computational Drug Discovery Methods
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- SARS-CoV-2 and COVID-19 Research
Papers in
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- Protein Structure and Dynamics 4
- Advanced Biosensing Techniques and Applications 2
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- Computational Drug Discovery Methods 12
- Co-authors
- Andrea R. Beccari (19 shared papers)Carmine Talarico (16 shared papers)Silvia Gervasoni (6 shared papers)Alessandro Pedretti (7 shared papers)Giulio Vistoli (7 shared papers)Carmen Cerchia (4 shared papers)Marica Gemei (3 shared papers)Philip Gribbon (4 shared papers)
In The Last Decade
Candida Manelfi
21 papers receiving 315 citations
Peers
Comparison fields: 5 of 77
- Computational Theory and Mathematics 155
- Infectious Diseases 95
- Pharmacology 21
- Molecular Biology 151
- Complementary and alternative medicine 15
Countries citing papers authored by Candida Manelfi
This map shows the geographic impact of Candida Manelfi'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 Candida Manelfi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Candida Manelfi more than expected).
Fields of papers citing papers by Candida Manelfi
This network shows the impact of papers produced by Candida Manelfi. 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 Candida Manelfi. The network helps show where Candida Manelfi may publish in the future.
Co-authors
The 25 scholars most cited alongside Candida Manelfi, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 57 | |
| 2 | 2020 | 45 | |
| 3 | 2021 | 37 | |
| 4 | 2020 | 25 | |
| 5 | 2018 | 24 | |
| 6 | 2018 | 21 | |
| 7 | 2020 | 20 | |
| 8 | 2021 | 16 | |
| 9 | 2021 | 15 | |
| 10 | 2022 | 12 | |
| 11 | 2023 | 10 | |
| 12 | 2024 | 9 | |
| 13 | 2021 | 6 | |
| 14 | 2022 | 6 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2022 | 3 | |
| 19 | 2020 | 2 | |
| 20 | 2024 | 1 |
About Candida Manelfi
Candida Manelfi is a scholar working on Molecular Biology, Computational Theory and Mathematics, Infectious Diseases, Cardiology and Cardiovascular Medicine and Materials Chemistry, having authored 21 papers that have together received 319 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Protein Structure and Dynamics (4 papers), Viral Infections and Immunology Research (3 papers), Machine Learning in Materials Science (3 papers), Viral gastroenteritis research and epidemiology (2 papers), Advanced Biosensing Techniques and Applications (2 papers) and PARP inhibition in cancer therapy (2 papers). The work is most often cited by research in Computational Theory and Mathematics (155 citations), Infectious Diseases (95 citations), Pharmacology (21 citations), Molecular Biology (151 citations) and Complementary and alternative medicine (15 citations). Candida Manelfi has collaborated with scholars based in Italy, Germany and Poland. Frequent co-authors include Andrea R. Beccari, Carmine Talarico, Silvia Gervasoni, Alessandro Pedretti, Giulio Vistoli, Carmen Cerchia, Marica Gemei, Philip Gribbon, Andrea Zaliani and Erik Lindahl. Their work appears in journals such as International Journal of Molecular Sciences, ACS Pharmacology & Translational Science, Journal of Cheminformatics, Bioinformatics and Cells.
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.