Cecilia Clementi
- Materials Chemistry top 1%
- Enzyme Structure and Function 30
- Machine Learning in Materials Science 20
- Molecular Biology top 1%
- Protein Structure and Dynamics 71
- RNA and protein synthesis mechanisms 12
- Structural Biology top 2%
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 11
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- Spectroscopy and Quantum Chemical Studies 18
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- Theoretical and Computational Physics 10
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- Mass Spectrometry Techniques and Applications 8
- Co-authors
- José N. OnuchicFrank NoéHugh NymeyerLydia E. KavrakiWenwei ZhengMary A. RohrdanzSilvina MatysiakPatricia A. Jennings
- Journals
- Chemical Reviews (2 papers)Proceedings of the National Academy of Sciences (11 papers)Journal of the American Chemical Society (1 paper)
- Partner nations
- United StatesGermanyItaly
In The Last Decade
Cecilia Clementi
108 papers receiving 7.1k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Materials Chemistry 3.5k
- Molecular Biology 5.2k
- Structural Biology 77
- Statistical and Nonlinear Physics 644
- Computational Theory and Mathematics 744
Countries citing papers authored by Cecilia Clementi
This map shows the geographic impact of Cecilia Clementi'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 Cecilia Clementi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cecilia Clementi more than expected).
Fields of papers citing papers by Cecilia Clementi
This network shows the impact of papers produced by Cecilia Clementi. 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 Cecilia Clementi. The network helps show where Cecilia Clementi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Cecilia Clementi, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2022 | 15 | |
| 5 | 2022 | 33 | |
| 6 | 2021 | 41 | |
| 7 | 2021 | 35 | |
| 8 | 2020 | 38 | |
| 9 | 2019 | 13 | |
| 10 | 2018 | 18 | |
| 11 | 2017 | 68 | |
| 12 | 2014 | 5 | |
| 13 | 2008 | 18 | |
| 14 | 2006 | 32 | |
| 15 | 2006 | 48 | |
| 16 | 2006 | 8 | |
| 17 | 2004 | 139 | |
| 18 | How native state topology affects the folding of Dihydrofolate Reductase and Interleukin-1β | 2000 | 7 |
| 19 | 1999 | 21 | |
| 20 | 1987 | 0 |
About Cecilia Clementi
Cecilia Clementi is a scholar working on Structural Biology, Molecular Biology and Materials Chemistry, having authored 110 papers that have together received 7.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (71 papers), Enzyme Structure and Function (30 papers), Machine Learning in Materials Science (20 papers), Spectroscopy and Quantum Chemical Studies (18 papers), RNA and protein synthesis mechanisms (12 papers), Computational Drug Discovery Methods (11 papers), Theoretical and Computational Physics (10 papers) and Mass Spectrometry Techniques and Applications (8 papers). The work is most often cited by research in Materials Chemistry (3.5k citations), Molecular Biology (5.2k citations) and Structural Biology (77 citations). Cecilia Clementi has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include José N. Onuchic, Frank Noé, Hugh Nymeyer, Lydia E. Kavraki, Wenwei Zheng, Mary A. Rohrdanz, Silvina Matysiak, Patricia A. Jennings, Payel Das and Marco Pettini. Their work appears in journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.