Filippo Pullara
Impact in
- Health Informatics top 5%
- Biophysics top 10%
Papers in
-
- Protein Structure and Dynamics 7
- Single-cell and spatial transcriptomics 2
- RNA and protein synthesis mechanisms 2
- Prion Diseases and Protein Misfolding 2
-
- Enzyme Structure and Function 4
- Co-authors
- Antonio Emanuele (2 shared papers)Valeria Militello (1 shared paper)Carlo Casarino (1 shared paper)Maurizio Leone (1 shared paper)D. Lansing Taylor (5 shared papers)Jeffrey L. Fine (3 shared papers)Akif Burak Tosun (3 shared papers)Michael J. Becich (3 shared papers)
- Journals
- Nature Communications (1 paper)Protein Expression and Purification (1 paper)Journal of Crystal Growth (1 paper)AIP Advances (1 paper)Redox Biology (1 paper)
- Partner nations
- United StatesItalyArgentina
In The Last Decade
Filippo Pullara
18 papers receiving 555 citations
Peers
Comparison fields: 5 of 103
- Health Informatics 23
- Biophysics 31
- Molecular Biology 321
- Food Science 77
- Surfaces, Coatings and Films 26
Countries citing papers authored by Filippo Pullara
This map shows the geographic impact of Filippo Pullara'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 Filippo Pullara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Filippo Pullara more than expected).
Fields of papers citing papers by Filippo Pullara
This network shows the impact of papers produced by Filippo Pullara. 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 Filippo Pullara. The network helps show where Filippo Pullara may publish in the future.
Co-authors
The 25 scholars most cited alongside Filippo Pullara, 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 | 2004 | 278 | |
| 2 | 2015 | 82 | |
| 3 | 2020 | 62 | |
| 4 | 2015 | 27 | |
| 5 | 2020 | 25 | |
| 6 | 2007 | 16 | |
| 7 | 2012 | 13 | |
| 8 | 2020 | 12 | |
| 9 | 2004 | 10 | |
| 10 | 2019 | 7 | |
| 11 | 2024 | 6 | |
| 12 | 2008 | 6 | |
| 13 | 2024 | 6 | |
| 14 | 2008 | 5 | |
| 15 | 2017 | 4 | |
| 16 | 2021 | 3 | |
| 17 | 2015 | 2 | |
| 18 | 2022 | 1 |
About Filippo Pullara
Filippo Pullara is a scholar working on Molecular Biology, Materials Chemistry, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics, having authored 18 papers that have together received 565 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Enzyme Structure and Function (4 papers), Digital Imaging for Blood Diseases (2 papers), Single-cell and spatial transcriptomics (2 papers), RNA and protein synthesis mechanisms (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Prion Diseases and Protein Misfolding (2 papers) and Spectroscopy and Quantum Chemical Studies (2 papers). The work is most often cited by research in Health Informatics (23 citations), Biophysics (31 citations), Molecular Biology (321 citations), Food Science (77 citations) and Surfaces, Coatings and Films (26 citations). Filippo Pullara has collaborated with scholars based in United States, Italy and Argentina. Frequent co-authors include Antonio Emanuele, Valeria Militello, Carlo Casarino, Maurizio Leone, D. Lansing Taylor, Jeffrey L. Fine, Akif Burak Tosun, Michael J. Becich, Guillermo Calero and M. U. Palma. Their work appears in journals such as Nature Communications, Protein Expression and Purification, Journal of Crystal Growth, AIP Advances and Redox Biology.
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.