Jonas Reeb
Impact in
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- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- Biomedical Text Mining and Ontologies
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- Genomics and Rare Diseases
Papers in
- Genetics 5
- Genomics and Rare Diseases 3
- Genetic Associations and Epidemiology 2
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- Machine Learning in Bioinformatics 3
- Protein Structure and Dynamics 1
- Biomedical Text Mining and Ontologies 1
- Genomics and Phylogenetic Studies 1
- Bioinformatics and Genomic Networks 1
- Co-authors
- Burkhard Rost (5 shared papers)Michael Bernhofer (2 shared papers)Edda Kloppmann (2 shared papers)Maximilian Hecht (2 shared papers)Yannick Mahlich (2 shared papers)Yana Bromberg (2 shared papers)Lindsay R. Stolzenburg (1 shared paper)Ammar J. Alsheikh (1 shared paper)
- Journals
- Proteins Structure Function and Bioinformatics (2 papers)Nucleic Acids Research (1 paper)BMC Bioinformatics (1 paper)iScience (1 paper)Genome biology (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Jonas Reeb
9 papers receiving 712 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 507
- Genetics 97
- Endocrinology 13
- Plant Science 89
- Biotechnology 9
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 | 2019 | 315 | |
| 2 | 2014 | 246 | |
| 3 | 2022 | 42 | |
| 4 | 2016 | 38 | |
| 5 | 2020 | 26 | |
| 6 | 2014 | 24 | |
| 7 | 2017 | 15 | |
| 8 | 2016 | 12 | |
| 9 | 2023 | 1 |
About Jonas Reeb
Jonas Reeb is a scholar working on Genetics, Molecular Biology, Oncology, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 9 papers that have together received 719 indexed citations. Recurring topics across this work include Genomics and Rare Diseases (3 papers), Machine Learning in Bioinformatics (3 papers), Genetic Associations and Epidemiology (2 papers), Cancer Immunotherapy and Biomarkers (1 paper), Protein Structure and Dynamics (1 paper), Biomedical Text Mining and Ontologies (1 paper), Genomics and Phylogenetic Studies (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Molecular Biology (507 citations), Genetics (97 citations), Endocrinology (13 citations), Plant Science (89 citations) and Biotechnology (9 citations). Jonas Reeb has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Burkhard Rost, Michael Bernhofer, Edda Kloppmann, Maximilian Hecht, Yannick Mahlich, Yana Bromberg, Lindsay R. Stolzenburg, Ammar J. Alsheikh, Jozef Lazar and J. Wade Davis. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Nucleic Acids Research, BMC Bioinformatics, iScience and Genome biology.
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.