Csaba Miskey
Impact in
Papers in
- Genetics 23
- Virus-based gene therapy research 17
- Animal Genetics and Reproduction 6
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- CRISPR and Genetic Engineering 12
- Retinal Development and Disorders 3
- Co-authors
- Zoltán Ivics (49 shared papers)Zsuzsanna Izsvák (21 shared papers)Lajos Mátés (5 shared papers)Andreas Gogol‐Döring (7 shared papers)Dawid P. Grzela (1 shared paper)Eyayu Belay (1 shared paper)Ermira Samara-Kuko (1 shared paper)Boris Jerchow (1 shared paper)
- Journals
- Nucleic Acids Research (7 papers)Molecular Therapy (6 papers)Mobile DNA (3 papers)Molecular Therapy — Nucleic Acids (2 papers)International Journal of Molecular Sciences (2 papers)
- Partner nations
- GermanyHungaryUnited States
In The Last Decade
Csaba Miskey
58 papers receiving 2.8k citations
Csaba Miskey's Hit Papers
Peers
Comparison fields: 5 of 85
- Genetics 974
- Oncology 462
- Molecular Biology 1.1k
- Plant Science 457
- Virology 36
Countries citing papers authored by Csaba Miskey
This map shows the geographic impact of Csaba Miskey'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 Csaba Miskey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Csaba Miskey more than expected).
Fields of papers citing papers by Csaba Miskey
This network shows the impact of papers produced by Csaba Miskey. 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 Csaba Miskey. The network helps show where Csaba Miskey may publish in the future.
Co-authors
The 25 scholars most cited alongside Csaba Miskey, 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Molecular evolution of a novel hyperactive Sleeping Beauty transposase enables robust stable gene transfer in vertebrates Hit paper breakdown → | 2009 | 773 |
| 2 | 2016 | 216 | |
| 3 | 2003 | 140 | |
| 4 | 2016 | 137 | |
| 5 | 2019 | 109 | |
| 6 | 2007 | 95 | |
| 7 | 2005 | 93 | |
| 8 | 2016 | 92 | |
| 9 | 2007 | 78 | |
| 10 | 2019 | 78 | |
| 11 | 2011 | 72 | |
| 12 | 2004 | 60 | |
| 13 | 2018 | 60 | |
| 14 | 2012 | 57 | |
| 15 | 2012 | 53 | |
| 16 | 2020 | 53 | |
| 17 | 2009 | 52 | |
| 18 | 2019 | 52 | |
| 19 | 2024 | 40 | |
| 20 | 2018 | 37 |
About Csaba Miskey
Csaba Miskey is a scholar working on Genetics, Molecular Biology, Oncology, Plant Science and Hepatology, having authored 60 papers that have together received 2.8k indexed citations. Recurring topics across this work include Virus-based gene therapy research (17 papers), Chromosomal and Genetic Variations (13 papers), CRISPR and Genetic Engineering (12 papers), CAR-T cell therapy research (8 papers), Animal Genetics and Reproduction (6 papers), Hepatitis C virus research (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers) and Retinal Development and Disorders (3 papers). The work is most often cited by research in Genetics (974 citations), Oncology (462 citations), Molecular Biology (1.1k citations), Plant Science (457 citations) and Virology (36 citations). Csaba Miskey has collaborated with scholars based in Germany, Hungary and United States. Frequent co-authors include Zoltán Ivics, Zsuzsanna Izsvák, Lajos Mátés, Andreas Gogol‐Döring, Dawid P. Grzela, Eyayu Belay, Ermira Samara-Kuko, Boris Jerchow, Janka Mátrai and Katja Becker. Their work appears in journals such as Nucleic Acids Research, Molecular Therapy, Mobile DNA, Molecular Therapy — Nucleic Acids and International Journal of Molecular Sciences.
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.