Daniel Havelka
Impact in
- Physiology top 5%
- Biofield Effects and Biophysics
- Magnetic and Electromagnetic Effects
- Biophysics top 5%
- Electromagnetic Fields and Biological Effects
Papers in
- Cell Biology 12
- Microtubule and mitosis dynamics 12
- Physiology 11
- Magnetic and Electromagnetic Effects 11
- Biofield Effects and Biophysics 8
- Co-authors
- Michal Cifra (31 shared papers)Ondřej Kučera (11 shared papers)J. Pokorný (2 shared papers)Jan Vrba (4 shared papers)Marco A. Deriu (4 shared papers)Pavel Dráber (3 shared papers)Lucie Kubínová (3 shared papers)Ahmed T. Ayoub (2 shared papers)
- Journals
- Scientific Reports (5 papers)Sensors and Actuators B Chemical (3 papers)Biosystems (2 papers)Wave Motion (1 paper)Applied Physics Letters (1 paper)
- Partner nations
- CzechiaSwitzerlandItaly
In The Last Decade
Daniel Havelka
32 papers receiving 527 citations
Peers
Comparison fields: 5 of 70
- Physiology 86
- Biophysics 104
- Cell Biology 151
- Biotechnology 72
- Cellular and Molecular Neuroscience 117
Countries citing papers authored by Daniel Havelka
This map shows the geographic impact of Daniel Havelka'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 Daniel Havelka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Havelka more than expected).
Fields of papers citing papers by Daniel Havelka
This network shows the impact of papers produced by Daniel Havelka. 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 Daniel Havelka. The network helps show where Daniel Havelka may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Havelka, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 107 | |
| 2 | 2011 | 77 | |
| 3 | 2019 | 51 | |
| 4 | 2012 | 37 | |
| 5 | 2019 | 35 | |
| 6 | 2014 | 28 | |
| 7 | 2014 | 27 | |
| 8 | 2016 | 20 | |
| 9 | 2017 | 16 | |
| 10 | 2023 | 15 | |
| 11 | 2018 | 15 | |
| 12 | 2020 | 15 | |
| 13 | 2020 | 13 | |
| 14 | 2009 | 12 | |
| 15 | 2019 | 11 | |
| 16 | 2012 | 11 | |
| 17 | 2011 | 9 | |
| 18 | 2018 | 9 | |
| 19 | 2021 | 8 | |
| 20 | 2011 | 8 |
About Daniel Havelka
Daniel Havelka is a scholar working on Cell Biology, Physiology, Electrical and Electronic Engineering, Biomedical Engineering and Physiology, having authored 33 papers that have together received 555 indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (12 papers), Magnetic and Electromagnetic Effects (11 papers), Microwave Engineering and Waveguides (8 papers), Biofield Effects and Biophysics (8 papers), Microwave and Dielectric Measurement Techniques (8 papers), Photoreceptor and optogenetics research (7 papers), Microbial Inactivation Methods (5 papers) and Electromagnetic Fields and Biological Effects (5 papers). The work is most often cited by research in Physiology (86 citations), Biophysics (104 citations), Cell Biology (151 citations), Biotechnology (72 citations) and Cellular and Molecular Neuroscience (117 citations). Daniel Havelka has collaborated with scholars based in Czechia, Switzerland and Italy. Frequent co-authors include Michal Cifra, Ondřej Kučera, J. Pokorný, Jan Vrba, Marco A. Deriu, Pavel Dráber, Lucie Kubínová, Ahmed T. Ayoub, Jack A. Tuszyński and Vadym Sulimenko. Their work appears in journals such as Scientific Reports, Sensors and Actuators B Chemical, Biosystems, Wave Motion and Applied 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.