Ralf Eggeling
Impact in
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- SARS-CoV-2 and COVID-19 Research
- SARS-CoV-2 detection and testing
- Viral Infections and Outbreaks Research
- Viral Infections and Vectors
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- Genomics and Chromatin Dynamics
- RNA and protein synthesis mechanisms
- Gene expression and cancer classification
Papers in
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- Genomics and Chromatin Dynamics 5
- Gene expression and cancer classification 2
- Bioinformatics and Genomic Networks 2
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- Bayesian Modeling and Causal Inference 6
- Algorithms and Data Compression 2
- Co-authors
- Ivo Große (8 shared papers)Mikko Koivisto (7 shared papers)Teemu Roos (2 shared papers)Petri Myllymäki (2 shared papers)Nico Pfeifer (6 shared papers)Lutz Gieselmann (2 shared papers)Florian Klein (2 shared papers)Henning Gruell (2 shared papers)
In The Last Decade
Ralf Eggeling
20 papers receiving 256 citations
Peers
Comparison fields: 5 of 67
- Infectious Diseases 87
- Molecular Biology 112
- Health Informatics 2
- Modeling and Simulation 6
- Artificial Intelligence 39
Countries citing papers authored by Ralf Eggeling
This map shows the geographic impact of Ralf Eggeling'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 Eggeling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ralf Eggeling more than expected).
Fields of papers citing papers by Ralf Eggeling
This network shows the impact of papers produced by Ralf Eggeling. 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 Eggeling. The network helps show where Ralf Eggeling may publish in the future.
Co-authors
The 25 scholars most cited alongside Ralf Eggeling, 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 | 2019 | 67 | |
| 2 | 2021 | 45 | |
| 3 | 2015 | 30 | |
| 4 | 2014 | 20 | |
| 5 | 2019 | 17 | |
| 6 | 2016 | 13 | |
| 7 | 2018 | 13 | |
| 8 | 2021 | 9 | |
| 9 | 2019 | 8 | |
| 10 | 2013 | 6 | |
| 11 | 2021 | 5 | |
| 12 | Dealing with small data: On the generalization of context trees | 2015 | 5 |
| 13 | Robust learning of inhomogeneous PMMs | 2014 | 5 |
| 14 | Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth | 2018 | 5 |
| 15 | Pruning rules for learning parsimonious context trees | 2016 | 3 |
| 16 | Finding Optimal Bayesian Networks with Local Structure. | 2018 | 3 |
| 17 | On Structure Priors for Learning Bayesian Networks | 2019 | 2 |
| 18 | 2018 | 2 | |
| 19 | 2017 | 2 | |
| 20 | 2025 | 1 |
About Ralf Eggeling
Ralf Eggeling is a scholar working on Molecular Biology, Artificial Intelligence, Infectious Diseases, Information Systems and Management Science and Operations Research, having authored 21 papers that have together received 261 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (6 papers), Genomics and Chromatin Dynamics (5 papers), Gene expression and cancer classification (2 papers), Data Mining Algorithms and Applications (2 papers), Bioinformatics and Genomic Networks (2 papers), Algorithms and Data Compression (2 papers), Data Quality and Management (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Infectious Diseases (87 citations), Molecular Biology (112 citations), Health Informatics (2 citations), Modeling and Simulation (6 citations) and Artificial Intelligence (39 citations). Ralf Eggeling has collaborated with scholars based in Germany, Finland and Belgium. Frequent co-authors include Ivo Große, Mikko Koivisto, Teemu Roos, Petri Myllymäki, Nico Pfeifer, Lutz Gieselmann, Florian Klein, Henning Gruell, Verena Krähling and Christine Dahlke. Their work appears in journals such as Bioinformatics, Journal of Clinical Microbiology, Plant Molecular Biology, BMC Public Health and Machine Learning.
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.