Marko Marhl
Impact in
- Statistical and Nonlinear Physics top 0.5%
- stochastic dynamics and bifurcation
- Chaos control and synchronization
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- Nonlinear Dynamics and Pattern Formation
Papers in
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- Gene Regulatory Network Analysis 21
- Ion channel regulation and function 14
- Protein Structure and Dynamics 11
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- stochastic dynamics and bifurcation 27
- Co-authors
- Matjaž Perc (44 shared papers)Marko Gosak (40 shared papers)Stefan Schuster (13 shared papers)Rene Markovič (29 shared papers)Marjan Slak Rupnik (11 shared papers)Andraž Stožer (12 shared papers)Jurij Dolenšek (10 shared papers)Thomas Höfer (1 shared paper)
In The Last Decade
Marko Marhl
106 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 171
- Statistical and Nonlinear Physics 1.3k
- Computer Networks and Communications 795
- Cognitive Neuroscience 612
- Modeling and Simulation 121
- Cellular and Molecular Neuroscience 362
Countries citing papers authored by Marko Marhl
This map shows the geographic impact of Marko Marhl'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 Marko Marhl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marko Marhl more than expected).
Fields of papers citing papers by Marko Marhl
This network shows the impact of papers produced by Marko Marhl. 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 Marko Marhl. The network helps show where Marko Marhl may publish in the future.
Co-authors
The 25 scholars most cited alongside Marko Marhl, 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 109 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 325 | |
| 2 | 2002 | 294 | |
| 3 | 2004 | 168 | |
| 4 | 2013 | 137 | |
| 5 | 2000 | 118 | |
| 6 | 2006 | 112 | |
| 7 | 2003 | 90 | |
| 8 | 2005 | 84 | |
| 9 | 2007 | 79 | |
| 10 | 2007 | 77 | |
| 11 | 2020 | 75 | |
| 12 | 2005 | 71 | |
| 13 | 2021 | 63 | |
| 14 | 1998 | 58 | |
| 15 | 2008 | 55 | |
| 16 | 2001 | 54 | |
| 17 | 2015 | 51 | |
| 18 | 2012 | 51 | |
| 19 | 2009 | 46 | |
| 20 | 2003 | 41 |
About Marko Marhl
Marko Marhl is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Computer Networks and Communications, Surgery and Cognitive Neuroscience, having authored 109 papers that have together received 3.4k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (29 papers), stochastic dynamics and bifurcation (27 papers), Gene Regulatory Network Analysis (21 papers), Pancreatic function and diabetes (18 papers), Neural dynamics and brain function (18 papers), Ion channel regulation and function (14 papers), Photoreceptor and optogenetics research (12 papers) and Protein Structure and Dynamics (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.3k citations), Computer Networks and Communications (795 citations), Cognitive Neuroscience (612 citations), Modeling and Simulation (121 citations) and Cellular and Molecular Neuroscience (362 citations). Marko Marhl has collaborated with scholars based in Slovenia, Germany and Austria. Frequent co-authors include Matjaž Perc, Marko Gosak, Stefan Schuster, Rene Markovič, Marjan Slak Rupnik, Andraž Stožer, Jurij Dolenšek, Thomas Höfer, Vladimir Grubelnik and Milan Brumen. Their work appears in journals such as Biophysical Chemistry, Chaos Solitons & Fractals, Biosystems, Frontiers in Physiology and Chemical Physics 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.