Filippo Pullara
Impact in
- Health Informatics top 10%
- Biophysics top 10%
Papers in
-
- Protein Structure and Dynamics 7
- Prion Diseases and Protein Misfolding 2
- Bioinformatics and Genomic Networks 2
-
- Radiomics and Machine Learning in Medical Imaging 2
- Co-authors
- Antonio Emanuele (2 shared papers)Carlo Casarino (1 shared paper)Maurizio Leone (1 shared paper)Valeria Militello (1 shared paper)S. Chakra Chennubhotla (4 shared papers)D. Lansing Taylor (4 shared papers)Akif Burak Tosun (2 shared papers)Michael John Becich (2 shared papers)
- Journals
- Journal of Crystal Growth (1 paper)Cell Reports Methods (1 paper)The Journal of Physical Chemistry B (1 paper)AIP Advances (1 paper)Biophysical Chemistry (1 paper)
- Partner nations
- United StatesItalyArgentina
In The Last Decade
Filippo Pullara
17 papers receiving 576 citations
Peers
Comparison fields: 5 of 103
- Health Informatics 23
- Biophysics 34
- Molecular Biology 329
- Structural Biology 7
- Food Science 77
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 | 282 | |
| 2 | 2015 | 81 | |
| 3 | 2020 | 65 | |
| 4 | 2015 | 32 | |
| 5 | 2020 | 26 | |
| 6 | 2012 | 16 | |
| 7 | 2007 | 16 | |
| 8 | 2020 | 14 | |
| 9 | 2004 | 10 | |
| 10 | 2024 | 8 | |
| 11 | 2019 | 7 | |
| 12 | 2008 | 6 | |
| 13 | 2017 | 6 | |
| 14 | 2008 | 5 | |
| 15 | 2017 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 2015 | 2 |
About Filippo Pullara
Filippo Pullara is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Materials Chemistry, Physiology and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 582 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), Prion Diseases and Protein Misfolding (2 papers), Spectroscopy and Quantum Chemical Studies (2 papers), Bioinformatics and Genomic Networks (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (23 citations), Biophysics (34 citations), Molecular Biology (329 citations), Structural Biology (7 citations) and Food Science (77 citations). Filippo Pullara has collaborated with scholars based in United States, Italy and Argentina. Frequent co-authors include Antonio Emanuele, Carlo Casarino, Maurizio Leone, Valeria Militello, S. Chakra Chennubhotla, D. Lansing Taylor, Akif Burak Tosun, Michael John Becich, Jeffrey L. Fine and Guillermo A. Calero. Their work appears in journals such as Journal of Crystal Growth, Cell Reports Methods, The Journal of Physical Chemistry B, AIP Advances and Biophysical Chemistry.
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.