Patrick Erñst
- Neurology top 10%
- Molecular Biology top 10%
- RNA and protein synthesis mechanisms 10
- Biomedical Text Mining and Ontologies 7
- Mitochondrial Function and Pathology 6
- Protein Structure and Dynamics 5
- Genetics top 10%
- Ecology top 10%
- Microbiology top 10%
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- Monoclonal and Polyclonal Antibodies Research 7
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- Topic Modeling 6
- Semantic Web and Ontologies 6
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- Photoreceptor and optogenetics research 5
- Co-authors
- Andreas PlückthunGerhard WeikumAmy SiuPeer R. E. MittlLufang ZhouMagdalini PolymenidouFrédéric H.‐T. AllainPaolo Paganetti
- Cited by
- NeurologyMolecular BiologyGenetics
- Journals
- Nature Communications (4 papers)Scientific Reports (3 papers)Process Biochemistry (2 papers)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Patrick Erñst
47 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 113
- Neurology 171
- Molecular Biology 760
- Genetics 89
- Ecology 158
- Microbiology 37
Countries citing papers authored by Patrick Erñst
This map shows the geographic impact of Patrick Erñst'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 Patrick Erñst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Erñst more than expected).
Fields of papers citing papers by Patrick Erñst
This network shows the impact of papers produced by Patrick Erñst. 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 Patrick Erñst. The network helps show where Patrick Erñst may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Patrick Erñst, 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 | 1 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 10 | |
| 6 | 2021 | 33 | |
| 7 | 2021 | 44 | |
| 8 | 2021 | 41 | |
| 9 | 2021 | 6 | |
| 10 | 2020 | 17 | |
| 11 | 2020 | 29 | |
| 12 | 2019 | 150 | |
| 13 | 2019 | 26 | |
| 14 | 2018 | 10 | |
| 15 | 2017 | 13 | |
| 16 | 2017 | 51 | |
| 17 | 2017 | 242 | |
| 18 | 2016 | 15 | |
| 19 | 2015 | 1 | |
| 20 | 2015 | 93 |
About Patrick Erñst
Patrick Erñst is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Artificial Intelligence, having authored 47 papers that have together received 1.1k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (10 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Biomedical Text Mining and Ontologies (7 papers), Mitochondrial Function and Pathology (6 papers), Topic Modeling (6 papers), Semantic Web and Ontologies (6 papers), Photoreceptor and optogenetics research (5 papers) and Protein Structure and Dynamics (5 papers). The work is most often cited by research in Neurology (171 citations), Molecular Biology (760 citations) and Genetics (89 citations). Patrick Erñst has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Andreas Plückthun, Gerhard Weikum, Amy Siu, Peer R. E. Mittl, Lufang Zhou, Magdalini Polymenidou, Frédéric H.‐T. Allain, Paolo Paganetti, Zuzanna Maniecka and Tariq Afroz. Their work appears in journals such as Nature Communications, Scientific Reports, Process Biochemistry, Journal of Visualized Experiments and Journal of Molecular and Cellular Cardiology.
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.