Rene Markovič
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
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- Complex Network Analysis Techniques
- stochastic dynamics and bifurcation
- Opinion Dynamics and Social Influence
Papers in
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- Gene Regulatory Network Analysis 6
- Metabolism, Diabetes, and Cancer 3
- Protein Structure and Dynamics 3
- Surgery 12
- Pancreatic function and diabetes 12
- Co-authors
- Marko Marhl (30 shared papers)Marko Gosak (24 shared papers)Matjaž Perc (12 shared papers)Jurij Dolenšek (11 shared papers)Andraž Stožer (11 shared papers)Marjan Slak Rupnik (7 shared papers)Vladimir Grubelnik (12 shared papers)Maja Duh (1 shared paper)
In The Last Decade
Rene Markovič
35 papers receiving 964 citations
Peers
Comparison fields: 5 of 130
- Modeling and Simulation 107
- Statistical and Nonlinear Physics 249
- Cognitive Neuroscience 148
- Endocrinology, Diabetes and Metabolism 99
- Surgery 245
Countries citing papers authored by Rene Markovič
This map shows the geographic impact of Rene Markovič'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 Rene Markovič with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rene Markovič more than expected).
Fields of papers citing papers by Rene Markovič
This network shows the impact of papers produced by Rene Markovič. 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 Rene Markovič. The network helps show where Rene Markovič may publish in the future.
Co-authors
The 25 scholars most cited alongside Rene Markovič, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 333 | |
| 2 | 2020 | 75 | |
| 3 | 2021 | 65 | |
| 4 | 2021 | 56 | |
| 5 | 2015 | 53 | |
| 6 | 2017 | 39 | |
| 7 | 2019 | 30 | |
| 8 | 2015 | 29 | |
| 9 | 2020 | 26 | |
| 10 | 2021 | 24 | |
| 11 | 2020 | 22 | |
| 12 | 2020 | 21 | |
| 13 | 2022 | 20 | |
| 14 | 2015 | 20 | |
| 15 | 2015 | 20 | |
| 16 | 2011 | 18 | |
| 17 | 2019 | 17 | |
| 18 | 2018 | 16 | |
| 19 | 2020 | 13 | |
| 20 | 2018 | 12 |
About Rene Markovič
Rene Markovič is a scholar working on Molecular Biology, Surgery, Statistical and Nonlinear Physics, Computer Networks and Communications and Cognitive Neuroscience, having authored 36 papers that have together received 973 indexed citations. Recurring topics across this work include Pancreatic function and diabetes (12 papers), Gene Regulatory Network Analysis (6 papers), Nonlinear Dynamics and Pattern Formation (4 papers), Neural dynamics and brain function (4 papers), Diabetes Management and Research (3 papers), Advanced Thermodynamics and Statistical Mechanics (3 papers), Metabolism, Diabetes, and Cancer (3 papers) and Protein Structure and Dynamics (3 papers). The work is most often cited by research in Modeling and Simulation (107 citations), Statistical and Nonlinear Physics (249 citations), Cognitive Neuroscience (148 citations), Endocrinology, Diabetes and Metabolism (99 citations) and Surgery (245 citations). Rene Markovič has collaborated with scholars based in Slovenia, Austria and Taiwan. Frequent co-authors include Marko Marhl, Marko Gosak, Matjaž Perc, Jurij Dolenšek, Andraž Stožer, Marjan Slak Rupnik, Vladimir Grubelnik, Maja Duh, Maša Skelin Klemen and Milan Brumen. Their work appears in journals such as Frontiers in Physiology, Chaos Solitons & Fractals, Physics of Life Reviews, PLoS ONE and Physica A Statistical Mechanics and its Applications.
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.