Martin Pirkl
Impact in
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- Cancer Cells and Metastasis
Papers in
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- HIV/AIDS drug development and treatment 3
- Parvovirus B19 Infection Studies 2
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- Gene Regulatory Network Analysis 2
- CRISPR and Genetic Engineering 2
- Co-authors
- Niko Beerenwinkel (7 shared papers)Nina Frey (1 shared paper)Gerhard Rogler (1 shared paper)Femke Ringnalda (1 shared paper)Tuncay Baubec (1 shared paper)Sharan Janjuha (1 shared paper)Gerald Schwank (1 shared paper)Stefan Butz (1 shared paper)
- Journals
- Bioinformatics (5 papers)The Journal of Infectious Diseases (2 papers)Journal of Medical Virology (2 papers)The Journal of Clinical Endocrinology & Metabolism (1 paper)International Journal of Surgery (1 paper)
- Partner nations
- GermanySwitzerlandUnited Kingdom
In The Last Decade
Martin Pirkl
20 papers receiving 260 citations
Peers
Comparison fields: 5 of 61
- Aging 6
- Oncology 77
- Cancer Research 32
- Molecular Biology 135
- Biophysics 11
Countries citing papers authored by Martin Pirkl
This map shows the geographic impact of Martin Pirkl'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 Martin Pirkl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Pirkl more than expected).
Fields of papers citing papers by Martin Pirkl
This network shows the impact of papers produced by Martin Pirkl. 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 Martin Pirkl. The network helps show where Martin Pirkl may publish in the future.
Co-authors
The 25 scholars most cited alongside Martin Pirkl, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 157 | |
| 2 | 2021 | 19 | |
| 3 | 2015 | 14 | |
| 4 | 2017 | 11 | |
| 5 | 2024 | 9 | |
| 6 | 2018 | 8 | |
| 7 | 1995 | 8 | |
| 8 | From research to application: How phased array radars conquered the real world | 2013 | 6 |
| 9 | 2021 | 6 | |
| 10 | 1997 | 6 | |
| 11 | 2023 | 5 | |
| 12 | 2024 | 4 | |
| 13 | 2024 | 4 | |
| 14 | 2022 | 3 | |
| 15 | 2022 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2023 | 1 | |
| 19 | 2022 | 1 | |
| 20 | 2021 | 1 |
About Martin Pirkl
Martin Pirkl is a scholar working on Infectious Diseases, Molecular Biology, Virology, Aerospace Engineering and Hepatology, having authored 22 papers that have together received 269 indexed citations. Recurring topics across this work include HIV Research and Treatment (4 papers), HIV/AIDS drug development and treatment (3 papers), Hepatitis C virus research (3 papers), Parvovirus B19 Infection Studies (2 papers), Radar Systems and Signal Processing (2 papers), Gene Regulatory Network Analysis (2 papers), CRISPR and Genetic Engineering (2 papers) and Animal Virus Infections Studies (2 papers). The work is most often cited by research in Aging (6 citations), Oncology (77 citations), Cancer Research (32 citations), Molecular Biology (135 citations) and Biophysics (11 citations). Martin Pirkl has collaborated with scholars based in Germany, Switzerland and United Kingdom. Frequent co-authors include Niko Beerenwinkel, Nina Frey, Gerhard Rogler, Femke Ringnalda, Tuncay Baubec, Sharan Janjuha, Gerald Schwank, Stefan Butz, Giancarlo Russo and Sumana Srivatsa. Their work appears in journals such as Bioinformatics, The Journal of Infectious Diseases, Journal of Medical Virology, The Journal of Clinical Endocrinology & Metabolism and International Journal of Surgery.
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.