A. Gamba

75 papers receiving 1.1k citations

Peers

A. Gamba
Comparison fields: 5 of 116
  • Modeling and Simulation 226
  • Cell Biology 249
  • Statistical and Nonlinear Physics 162
  • Applied Mathematics 91
  • Nuclear and High Energy Physics 108
Replace Pavel M. Lushnikov with:
Pavel M. Lushnikov United States
Shankar C. Venkataramani United States
Mario Markus Germany
V. N. Biktashev United Kingdom
Gilberto L. Thomas Brazil
R. Leféver Belgium
M. A. Tsyganov Russia
Alexei F. Cheviakov Canada
L. P. Kok Netherlands
Idán Tuval Spain
A. Gamba relative to Pavel M. Lushnikov United States Pavel M. Lushnikov's profile →
Citations per field
00.5×3.1×
Pavel M. Lushnikov · 1×
Citations per year

Countries citing papers authored by A. Gamba

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with A. Gamba Line = papers co-authored together A. Gamba links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003187
2 200574
3 200465
4 195957
5 196752
6 200443
7 201341
8 200133
9 196730
10 201229
11 195928
12 201228
13 201526
14 200426
15 197523
16 200921
17 200719
18 196517
19 196817
20 199415

About A. Gamba

A. Gamba is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics, Cell Biology and Modeling and Simulation, having authored 77 papers that have together received 1.1k indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (9 papers), Cellular Mechanics and Interactions (8 papers), Advanced Thermodynamics and Statistical Mechanics (7 papers), Lipid Membrane Structure and Behavior (6 papers), Quantum Mechanics and Applications (5 papers), Crystallography and Radiation Phenomena (5 papers), Advanced NMR Techniques and Applications (4 papers) and Cosmology and Gravitation Theories (4 papers). The work is most often cited by research in Modeling and Simulation (226 citations), Cell Biology (249 citations), Statistical and Nonlinear Physics (162 citations), Applied Mathematics (91 citations) and Nuclear and High Energy Physics (108 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, A. de Candia, Antonio Coniglio, D. Ambrosi, Luigi Preziosi, G. Boffetta, I. V. Kolokolov and F. De Lillo. Their work appears in journals such as Physical Review Letters, Journal of Statistical Physics, Physics Letters A, Physics Letters B and Proceedings of the National Academy of Sciences.

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.

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