Dzmitry Afanasenkau
-
- Neuroscience and Neural Engineering 7
- Photoreceptor and optogenetics research 2
-
- thermodynamics and calorimetric analyses 3
-
- Field-Flow Fractionation Techniques 3
-
- Neural dynamics and brain function 4
- EEG and Brain-Computer Interfaces 2
-
- Lipid Membrane Structure and Behavior 3
- RNA Interference and Gene Delivery 2
Dzmitry Afanasenkau
17 papers receiving 318 citations
Peers
Comparison fields: 5 of 69
- Cellular and Molecular Neuroscience 111
- Physical and Theoretical Chemistry 46
- Biomedical Engineering 142
- Computational Mechanics 61
- Statistical and Nonlinear Physics 30
Countries citing papers authored by Dzmitry Afanasenkau
This map shows the geographic impact of Dzmitry Afanasenkau'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 Dzmitry Afanasenkau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dzmitry Afanasenkau more than expected).
Fields of papers citing papers by Dzmitry Afanasenkau
This network shows the impact of papers produced by Dzmitry Afanasenkau. 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 Dzmitry Afanasenkau. The network helps show where Dzmitry Afanasenkau may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dzmitry Afanasenkau, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 1 | |
| 4 | 2021 | 10 | |
| 5 | 2020 | 107 | |
| 6 | 2020 | 12 | |
| 7 | 2019 | 23 | |
| 8 | 2018 | 2 | |
| 9 | 2016 | 21 | |
| 10 | 2016 | 14 | |
| 11 | 2016 | 73 | |
| 12 | 2014 | 5 | |
| 13 | 2014 | 9 | |
| 14 | Supported lipid bilayer as a biomimetic platform for neuronal cell culture | 2013 | 5 |
| 15 | 2013 | 8 | |
| 16 | 2012 | 21 | |
| 17 | 2010 | 4 |
About Dzmitry Afanasenkau
Dzmitry Afanasenkau is a scholar working on Cellular and Molecular Neuroscience, Physical and Theoretical Chemistry, Cognitive Neuroscience, Bioengineering and Electrochemistry, having authored 17 papers that have together received 320 indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (7 papers), Neural dynamics and brain function (4 papers), thermodynamics and calorimetric analyses (3 papers), Field-Flow Fractionation Techniques (3 papers), Lipid Membrane Structure and Behavior (3 papers), Photoreceptor and optogenetics research (2 papers), EEG and Brain-Computer Interfaces (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (111 citations), Physical and Theoretical Chemistry (46 citations), Biomedical Engineering (142 citations), Computational Mechanics (61 citations) and Statistical and Nonlinear Physics (30 citations). Dzmitry Afanasenkau has collaborated with scholars based in Germany, United Kingdom and Sweden. Frequent co-authors include Simone Wiegand, Ivan R. Minev, Doreen Niether, Jan K. G. Dhont, Andreas Offenhäusser, Christoph Tondera, Pavel Musienko, Natalia Pavlova, Natalia Merkulyeva and Allan V. Kalueff. Their work appears in journals such as Langmuir, npj Flexible Electronics, Scientific Reports, Advanced Materials Technologies and Neuroscience Research.
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.