Carmelo Tempra
Impact in
- Physiology top 10%
- Alzheimer's disease research and treatments
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- Supramolecular Self-Assembly in Materials
Papers in
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- Lipid Membrane Structure and Behavior 9
- Protein Structure and Dynamics 8
- RNA Interference and Gene Delivery 3
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- Spectroscopy and Quantum Chemical Studies 5
- Co-authors
- Carmelo La Rosa (6 shared papers)Federica Scollo (5 shared papers)Danilo Milardi (4 shared papers)Michele F. M. Sciacca (3 shared papers)Fabio Lolicato (7 shared papers)Antonio Raudino (2 shared papers)Matti Javanainen (7 shared papers)O. H. Samuli Ollila (2 shared papers)
In The Last Decade
Carmelo Tempra
21 papers receiving 595 citations
Peers
Comparison fields: 5 of 93
- Physiology 285
- Biomaterials 88
- Molecular Biology 340
- Filtration and Separation 8
- Cell Biology 59
Countries citing papers authored by Carmelo Tempra
This map shows the geographic impact of Carmelo Tempra'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 Carmelo Tempra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carmelo Tempra more than expected).
Fields of papers citing papers by Carmelo Tempra
This network shows the impact of papers produced by Carmelo Tempra. 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 Carmelo Tempra. The network helps show where Carmelo Tempra may publish in the future.
Co-authors
The 25 scholars most cited alongside Carmelo Tempra, 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 | 2020 | 125 | |
| 2 | 2018 | 119 | |
| 3 | 2018 | 76 | |
| 4 | 2022 | 43 | |
| 5 | 2018 | 29 | |
| 6 | 2021 | 27 | |
| 7 | 2020 | 25 | |
| 8 | 2024 | 25 | |
| 9 | 2022 | 23 | |
| 10 | 2022 | 21 | |
| 11 | 2022 | 21 | |
| 12 | 2023 | 16 | |
| 13 | 2022 | 11 | |
| 14 | 2021 | 10 | |
| 15 | 2021 | 8 | |
| 16 | 2023 | 5 | |
| 17 | 2023 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2024 | 1 | |
| 20 | 2024 | 1 |
About Carmelo Tempra
Carmelo Tempra is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics, Physiology, Spectroscopy and Biomedical Engineering, having authored 21 papers that have together received 596 indexed citations. Recurring topics across this work include Lipid Membrane Structure and Behavior (9 papers), Protein Structure and Dynamics (8 papers), Alzheimer's disease research and treatments (6 papers), Spectroscopy and Quantum Chemical Studies (5 papers), RNA Interference and Gene Delivery (3 papers), Advanced NMR Techniques and Applications (3 papers), Mass Spectrometry Techniques and Applications (3 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Physiology (285 citations), Biomaterials (88 citations), Molecular Biology (340 citations), Filtration and Separation (8 citations) and Cell Biology (59 citations). Carmelo Tempra has collaborated with scholars based in Czechia, Finland and Germany. Frequent co-authors include Carmelo La Rosa, Federica Scollo, Danilo Milardi, Michele F. M. Sciacca, Fabio Lolicato, Antonio Raudino, Matti Javanainen, O. H. Samuli Ollila, Sara García‐Viñuales and Pavel Jungwirth. Their work appears in journals such as The Journal of Physical Chemistry B, Physical Chemistry Chemical Physics, Biochimica et Biophysica Acta (BBA) - Biomembranes, Journal of Chemical Theory and Computation and Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics.
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.