A. Gamba
Impact in
- Modeling and Simulation top 1%
- Mathematical Biology Tumor Growth
- Cell Biology top 5%
- Cellular Mechanics and Interactions
Papers in
-
- Lipid Membrane Structure and Behavior 6
- Angiogenesis and VEGF in Cancer 5
-
- Advanced Thermodynamics and Statistical Mechanics 7
- Co-authors
- Guido Serini (12 shared papers)Stefano Di Talia (5 shared papers)Federico Bussolino (5 shared papers)D. Ambrosi (2 shared papers)Antonio Coniglio (4 shared papers)A. de Candia (4 shared papers)Luigi Preziosi (2 shared papers)G. Boffetta (2 shared papers)
- Journals
- Physical Review Letters (4 papers)Physics Letters A (3 papers)Journal of Statistical Physics (3 papers)Physics Letters B (3 papers)Soft Matter (2 papers)
- Partner nations
- ItalyUnited StatesRussia
In The Last Decade
A. Gamba
76 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 120
- Modeling and Simulation 254
- Cell Biology 268
- Statistical and Nonlinear Physics 168
- Applied Mathematics 94
- Nuclear and High Energy Physics 111
Countries citing papers authored by A. Gamba
This map shows the geographic impact of A. Gamba'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 A. Gamba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Gamba more than expected).
Fields of papers citing papers by A. Gamba
This network shows the impact of papers produced by A. Gamba. 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 A. Gamba. The network helps show where A. Gamba may publish in the future.
Co-authors
The 25 scholars most cited alongside A. Gamba, 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 80 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 208 | |
| 2 | 2005 | 77 | |
| 3 | 2004 | 65 | |
| 4 | 1959 | 61 | |
| 5 | 1967 | 52 | |
| 6 | 2004 | 51 | |
| 7 | 2013 | 43 | |
| 8 | 2001 | 39 | |
| 9 | 1967 | 32 | |
| 10 | 2012 | 31 | |
| 11 | 2012 | 30 | |
| 12 | 2004 | 30 | |
| 13 | 2015 | 29 | |
| 14 | 1959 | 29 | |
| 15 | 1975 | 23 | |
| 16 | 2009 | 22 | |
| 17 | 2007 | 19 | |
| 18 | 1968 | 18 | |
| 19 | 1965 | 18 | |
| 20 | 2012 | 17 |
About A. Gamba
A. Gamba is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics, Modeling and Simulation and Cell Biology, having authored 80 papers that have together received 1.2k indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (11 papers), Cellular Mechanics and Interactions (9 papers), Advanced Thermodynamics and Statistical Mechanics (7 papers), Lipid Membrane Structure and Behavior (6 papers), Quantum Mechanics and Applications (5 papers), Angiogenesis and VEGF in Cancer (5 papers), Crystallography and Radiation Phenomena (5 papers) and Black Holes and Theoretical Physics (4 papers). The work is most often cited by research in Modeling and Simulation (254 citations), Cell Biology (268 citations), Statistical and Nonlinear Physics (168 citations), Applied Mathematics (94 citations) and Nuclear and High Energy Physics (111 citations). A. Gamba has collaborated with scholars based in Italy, United States and Russia. Frequent co-authors include Guido Serini, Stefano Di Talia, Federico Bussolino, D. Ambrosi, Antonio Coniglio, A. de Candia, Luigi Preziosi, G. Boffetta, Enrico Giraudo and I. V. Kolokolov. Their work appears in journals such as Physical Review Letters, Physics Letters A, Journal of Statistical Physics, Physics Letters B and Soft Matter.
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.