Jonas Reeb
Impact in
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- Genomics and Rare Diseases
- Genetic Associations and Epidemiology
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- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- CRISPR and Genetic Engineering
- Genomics and Chromatin Dynamics
Papers in
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- RNA and protein synthesis mechanisms 4
- Genomics and Phylogenetic Studies 3
- Machine Learning in Bioinformatics 2
- Protein Structure and Dynamics 1
- Genetics 5
- Genomics and Rare Diseases 4
- Genetic Associations and Epidemiology 2
- Co-authors
- Burkhard Rost (5 shared papers)Edda Kloppmann (2 shared papers)Michael Bernhofer (2 shared papers)Yana Bromberg (2 shared papers)Maximilian Hecht (2 shared papers)Yannick Mahlich (2 shared papers)Sujana Ghosh (1 shared paper)J. Wade Davis (1 shared paper)
- Journals
- Proteins Structure Function and Bioinformatics (2 papers)iScience (1 paper)Scientific Reports (1 paper)PLoS Computational Biology (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Jonas Reeb
6 papers receiving 150 citations
Peers
Comparison fields: 5 of 44
- Genetics 52
- Molecular Biology 116
- Endocrinology 5
- Cancer Research 9
- Immunology 10
Countries citing papers authored by Jonas Reeb
This map shows the geographic impact of Jonas Reeb'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 Jonas Reeb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonas Reeb more than expected).
Fields of papers citing papers by Jonas Reeb
This network shows the impact of papers produced by Jonas Reeb. 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 Jonas Reeb. The network helps show where Jonas Reeb may publish in the future.
Co-authors
The 20 scholars most cited alongside Jonas Reeb, 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 | 2022 | 39 | |
| 2 | 2016 | 36 | |
| 3 | 2020 | 25 | |
| 4 | 2014 | 22 | |
| 5 | 2017 | 16 | |
| 6 | 2016 | 12 | |
| 7 | 2023 | 0 |
About Jonas Reeb
Jonas Reeb is a scholar working on Molecular Biology, Genetics, Pulmonary and Respiratory Medicine, Cancer Research and Infectious Diseases, having authored 7 papers that have together received 150 indexed citations. Recurring topics across this work include Genomics and Rare Diseases (4 papers), RNA and protein synthesis mechanisms (4 papers), Genomics and Phylogenetic Studies (3 papers), Machine Learning in Bioinformatics (2 papers), Genetic Associations and Epidemiology (2 papers), Ferroptosis and cancer prognosis (1 paper), Cancer-related molecular mechanisms research (1 paper) and Protein Structure and Dynamics (1 paper). The work is most often cited by research in Genetics (52 citations), Molecular Biology (116 citations), Endocrinology (5 citations), Cancer Research (9 citations) and Immunology (10 citations). Jonas Reeb has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Burkhard Rost, Edda Kloppmann, Michael Bernhofer, Yana Bromberg, Maximilian Hecht, Yannick Mahlich, Sujana Ghosh, J. Wade Davis, Lindsay R. Stolzenburg and Howard J. Jacob. Their work appears in journals such as Proteins Structure Function and Bioinformatics, iScience, Scientific Reports, PLoS Computational Biology and BMC Bioinformatics.
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.