Imre Derényi
- Statistical and Nonlinear Physics top 0.05%
- Molecular Biology top 2%
- Computer Networks and Communications top 1%
- Artificial Intelligence top 1%
- Atomic and Molecular Physics, and Optics top 5%
- Co-authors
- Tamás VicsekGergely PallaIllés J. FarkasR. Dean AstumianAlbert-Ĺaszló BarabásiJacques ProstFrank JülicherGergely J. Szöllősi
- Topics
- stochastic dynamics and bifurcation (15 papers)Advanced Thermodynamics and Statistical Mechanics (13 papers)Lipid Membrane Structure and Behavior (11 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsComputational Theory and Mathematics
- Partner nations
- HungaryUnited StatesFrance
In The Last Decade
Imre Derényi
62 papers receiving 7.1k citations
Hit Papers
Peers
Comparison fields: 5 of 187
- Statistical and Nonlinear Physics 3.9k
- Molecular Biology 2.6k
- Computer Networks and Communications 1.2k
- Artificial Intelligence 947
- Atomic and Molecular Physics, and Optics 890
Countries citing papers authored by Imre Derényi
This map shows the geographic impact of Imre Derényi'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 Imre Derényi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Imre Derényi more than expected).
Fields of papers citing papers by Imre Derényi
This network shows the impact of papers produced by Imre Derényi. 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 Imre Derényi. The network helps show where Imre Derényi may publish in the future.
Co-authorship network of co-authors of Imre Derényi
This figure shows the co-authorship network connecting the top 25 collaborators of Imre Derényi. A scholar is included among the top collaborators of Imre Derényi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Imre Derényi. Imre Derényi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 9 | |
| 4 | 72 | |
| 5 | 44 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 8 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 38 | |
| 12 | 5 | |
| 13 | 14 | |
| 14 | Uncovering the overlapping community structure of complex networks in nature and societybreakdown → | 3468 |
| 15 | 125 | |
| 16 | 47 | |
| 17 | 41 | |
| 18 | 86 | |
| 19 | 296 | |
| 20 | 66 |
About Imre Derényi
Imre Derényi is a scholar working on Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics and Modeling and Simulation, having authored 63 papers that have together received 7.4k indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (15 papers), Advanced Thermodynamics and Statistical Mechanics (13 papers) and Lipid Membrane Structure and Behavior (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (3.9k citations), Computer Networks and Communications (1.2k citations) and Computational Theory and Mathematics (624 citations). Imre Derényi has collaborated with scholars based in Hungary, United States and France. Frequent co-authors include Tamás Vicsek, Gergely Palla, Illés J. Farkas, R. Dean Astumian, Albert-Ĺaszló Barabási, Jacques Prost, Frank Jülicher, Gergely J. Szöllősi, Martin Bier and Armand Ajdari. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.
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.