Ralf Mikut
Impact in
- Biophysics top 0.5%
- Cell Image Analysis Techniques
- Advanced Fluorescence Microscopy Techniques
- Microbiology top 1%
- Antimicrobial Peptides and Activities
Papers in
- Biophysics 31
- Cell Image Analysis Techniques 27
- Microbiology 16
- Antimicrobial Peptides and Activities 16
- Co-authors
- Markus ReischlVeit HagenmeyerKai HilpertLutz GröllJohannes StegmaierUwe SträhleJens JäkelJorge Ángel González Ordiano
- Journals
- PLoS ONE (11 papers)Scientific Reports (6 papers)Zebrafish (5 papers)Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (5 papers)IEEE Access (4 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Ralf Mikut
249 papers receiving 3.9k citations
Peers
Comparison fields: 5 of 193
- Biophysics 352
- Microbiology 367
- Cell Biology 423
- Artificial Intelligence 561
- Molecular Biology 1.2k
Countries citing papers authored by Ralf Mikut
This map shows the geographic impact of Ralf Mikut'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 Ralf Mikut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ralf Mikut more than expected).
Fields of papers citing papers by Ralf Mikut
This network shows the impact of papers produced by Ralf Mikut. 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 Ralf Mikut. The network helps show where Ralf Mikut may publish in the future.
Co-authors
The 25 scholars most cited alongside Ralf Mikut, 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 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 12 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 7 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 0 | |
| 10 | 2022 | 8 | |
| 11 | 2022 | 12 | |
| 12 | 2021 | 11 | |
| 13 | 2020 | 5 | |
| 14 | 2019 | 10 | |
| 15 | 2018 | 103 | |
| 16 | 2017 | 15 | |
| 17 | 2014 | 51 | |
| 18 | 2013 | 1 | |
| 19 | 2012 | 33 | |
| 20 | 2012 | 17 |
About Ralf Mikut
Ralf Mikut is a scholar working on Biophysics, Microbiology, Signal Processing, Media Technology and Artificial Intelligence, having authored 278 papers that have together received 4.0k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (34 papers), Cell Image Analysis Techniques (27 papers), Smart Grid Energy Management (24 papers), Zebrafish Biomedical Research Applications (20 papers), Time Series Analysis and Forecasting (19 papers), Antimicrobial Peptides and Activities (16 papers), Muscle activation and electromyography studies (15 papers) and Fuzzy Logic and Control Systems (15 papers). The work is most often cited by research in Biophysics (352 citations), Microbiology (367 citations), Cell Biology (423 citations), Artificial Intelligence (561 citations) and Molecular Biology (1.2k citations). Ralf Mikut has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Markus Reischl, Veit Hagenmeyer, Kai Hilpert, Lutz Gröll, Johannes Stegmaier, Uwe Strähle, Jens Jäkel, Jorge Ángel González Ordiano, Rüdiger Alshut and Simon Waczowicz. Their work appears in journals such as PLoS ONE, Scientific Reports, Zebrafish, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery and IEEE Access.
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.