Eva Dazert
Impact in
- Hepatology top 5%
- Hepatitis C virus research
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism
- Cancer, Lipids, and Metabolism
Papers in
-
- Bioinformatics and Genomic Networks 2
- PI3K/AKT/mTOR signaling in cancer 2
- DNA Repair Mechanisms 1
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- Cancer, Hypoxia, and Metabolism 4
- Cancer, Lipids, and Metabolism 3
- Co-authors
- Michael N. Hall (10 shared papers)Markus H. Heim (8 shared papers)Marco Colombi (6 shared papers)Suzette Moes (3 shared papers)Paul Jenoe (2 shared papers)Yakir Guri (1 shared paper)Howard Riezman (1 shared paper)Isabelle Riezman (1 shared paper)
- Journals
- International Journal of Molecular Sciences (2 papers)Proceedings of the National Academy of Sciences (2 papers)Bioinformatics (1 paper)Biomedicines (1 paper)Blood (1 paper)
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Eva Dazert
19 papers receiving 1.6k citations
Eva Dazert's Hit Papers
Peers
Comparison fields: 5 of 102
- Hepatology 246
- Cancer Research 316
- Aging 32
- Molecular Biology 820
- Immunology 235
Countries citing papers authored by Eva Dazert
This map shows the geographic impact of Eva Dazert'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 Eva Dazert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Dazert more than expected).
Fields of papers citing papers by Eva Dazert
This network shows the impact of papers produced by Eva Dazert. 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 Eva Dazert. The network helps show where Eva Dazert may publish in the future.
Co-authors
The 25 scholars most cited alongside Eva Dazert, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 383 | |
| 2 | 2017 | 311 | |
| 3 | Arginine reprograms metabolism in liver cancer via RBM39 Hit paper breakdown → | 2023 | 166 |
| 4 | 2012 | 151 | |
| 5 | 2012 | 112 | |
| 6 | 2009 | 107 | |
| 7 | 2022 | 93 | |
| 8 | 2016 | 58 | |
| 9 | 2014 | 48 | |
| 10 | 2021 | 47 | |
| 11 | 2015 | 43 | |
| 12 | 2009 | 28 | |
| 13 | 2022 | 20 | |
| 14 | 2019 | 19 | |
| 15 | 2022 | 10 | |
| 16 | 2025 | 3 | |
| 17 | 2024 | 3 | |
| 18 | 2025 | 2 | |
| 19 | 2007 | 2 | |
| 20 | 2016 | 0 |
About Eva Dazert
Eva Dazert is a scholar working on Molecular Biology, Cancer Research, Immunology, Oncology and Hepatology, having authored 21 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (4 papers), Cancer, Lipids, and Metabolism (3 papers), Cancer-related Molecular Pathways (2 papers), Hepatitis C virus research (2 papers), Acute Myeloid Leukemia Research (2 papers), Bioinformatics and Genomic Networks (2 papers), PI3K/AKT/mTOR signaling in cancer (2 papers) and DNA Repair Mechanisms (1 paper). The work is most often cited by research in Hepatology (246 citations), Cancer Research (316 citations), Aging (32 citations), Molecular Biology (820 citations) and Immunology (235 citations). Eva Dazert has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Michael N. Hall, Markus H. Heim, Marco Colombi, Suzette Moes, Paul Jenoe, Yakir Guri, Howard Riezman, Isabelle Riezman, Jason Roszik and Sravanth K. Hindupur. Their work appears in journals such as International Journal of Molecular Sciences, Proceedings of the National Academy of Sciences, Bioinformatics, Biomedicines and Blood.
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.