Aneta Koseska
- Computer Networks and Communications top 1%
- Statistical and Nonlinear Physics top 0.5%
- Molecular Biology
- Cognitive Neuroscience top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Co-authors
- Jürgen KurthsE.I. VolkovEvgenii VolkovPhilippe I. H. BastiaensJordi García‐OjalvoZoran NikoloskiSabrina HempelAlexey Zaikin
- Topics
- Gene Regulatory Network Analysis (23 papers)Nonlinear Dynamics and Pattern Formation (14 papers)stochastic dynamics and bifurcation (13 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsCognitive Neuroscience
- Partner nations
- GermanyRussiaUnited Kingdom
In The Last Decade
Aneta Koseska
39 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 103
- Computer Networks and Communications 984
- Statistical and Nonlinear Physics 812
- Molecular Biology 514
- Cognitive Neuroscience 273
- Atomic and Molecular Physics, and Optics 200
Countries citing papers authored by Aneta Koseska
This map shows the geographic impact of Aneta Koseska'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 Aneta Koseska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aneta Koseska more than expected).
Fields of papers citing papers by Aneta Koseska
This network shows the impact of papers produced by Aneta Koseska. 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 Aneta Koseska. The network helps show where Aneta Koseska may publish in the future.
Co-authorship network of co-authors of Aneta Koseska
This figure shows the co-authorship network connecting the top 25 collaborators of Aneta Koseska. A scholar is included among the top collaborators of Aneta Koseska 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 Aneta Koseska. Aneta Koseska is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 28 | |
| 5 | 20 | |
| 6 | 12 | |
| 7 | 36 | |
| 8 | 122 | |
| 9 | 53 | |
| 10 | 148 | |
| 11 | 21 | |
| 12 | 103 | |
| 13 | 14 | |
| 14 | 71 | |
| 15 | 14 | |
| 16 | 43 | |
| 17 | 73 | |
| 18 | 14 | |
| 19 | 74 | |
| 20 | 10 |
About Aneta Koseska
Aneta Koseska is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Molecular Biology, having authored 40 papers that have together received 1.7k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (23 papers), Nonlinear Dynamics and Pattern Formation (14 papers) and stochastic dynamics and bifurcation (13 papers). The work is most often cited by research in Statistical and Nonlinear Physics (812 citations), Computer Networks and Communications (984 citations) and Cognitive Neuroscience (273 citations). Aneta Koseska has collaborated with scholars based in Germany, Russia and United Kingdom. Frequent co-authors include Jürgen Kurths, E.I. Volkov, Evgenii Volkov, Philippe I. H. Bastiaens, Jordi García‐Ojalvo, Zoran Nikoloski, Sabrina Hempel, Alexey Zaikin, Anna Zakharova and Т. Е. Вадивасова. Their work appears in journals such as Physical Review Letters, Nature Communications and The EMBO Journal.
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.