John D. Bagert
Impact in
- Molecular Biology top 10%
- Genomics and Chromatin Dynamics
- Epigenetics and DNA Methylation
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- Protein Degradation and Inhibitors
- Chemical Synthesis and Analysis
- Ubiquitin and proteasome pathways
- Endocrinology top 10%
Papers in
-
- Protein Degradation and Inhibitors 7
- Genomics and Chromatin Dynamics 6
- Epigenetics and DNA Methylation 3
- Chromatin Remodeling and Cancer 3
- Bacterial biofilms and quorum sensing 2
-
- Click Chemistry and Applications 3
- Co-authors
- Tom W. Muir (8 shared papers)David A. Tirrell (5 shared papers)C. David Allis (4 shared papers)Lijuan Feng (2 shared papers)Benjamin A. Nacev (2 shared papers)Alborz Mahdavi (2 shared papers)Jianjiong Gao (1 shared paper)Alexey A. Soshnev (1 shared paper)
- Journals
- Journal of the American Chemical Society (3 papers)Nature (2 papers)Nature Communications (1 paper)Cell (1 paper)Nature Chemical Biology (1 paper)
- Partner nations
- United StatesGermanyDenmark
In The Last Decade
John D. Bagert
15 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 83
- Molecular Biology 955
- Endocrinology 50
- Organic Chemistry 217
- Oncology 134
- Cell Biology 87
Countries citing papers authored by John D. Bagert
This map shows the geographic impact of John D. Bagert'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 John D. Bagert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Bagert more than expected).
Fields of papers citing papers by John D. Bagert
This network shows the impact of papers produced by John D. Bagert. 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 John D. Bagert. The network helps show where John D. Bagert may publish in the future.
Co-authors
The 25 scholars most cited alongside John D. Bagert, 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 | 261 | |
| 2 | 2010 | 182 | |
| 3 | 2017 | 139 | |
| 4 | 2015 | 119 | |
| 5 | 2021 | 71 | |
| 6 | 2014 | 71 | |
| 7 | 2020 | 60 | |
| 8 | 2021 | 58 | |
| 9 | 2016 | 52 | |
| 10 | 2016 | 51 | |
| 11 | 2010 | 42 | |
| 12 | 2021 | 36 | |
| 13 | 2015 | 18 | |
| 14 | 2021 | 11 | |
| 15 | 2022 | 8 |
About John D. Bagert
John D. Bagert is a scholar working on Molecular Biology, Organic Chemistry, Cell Biology, Endocrinology and Biomedical Engineering, having authored 15 papers that have together received 1.2k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (7 papers), Genomics and Chromatin Dynamics (6 papers), Click Chemistry and Applications (3 papers), Epigenetics and DNA Methylation (3 papers), Chromatin Remodeling and Cancer (3 papers), Vibrio bacteria research studies (2 papers), Bacterial biofilms and quorum sensing (2 papers) and Biotin and Related Studies (2 papers). The work is most often cited by research in Molecular Biology (955 citations), Endocrinology (50 citations), Organic Chemistry (217 citations), Oncology (134 citations) and Cell Biology (87 citations). John D. Bagert has collaborated with scholars based in United States, Germany and Denmark. Frequent co-authors include Tom W. Muir, David A. Tirrell, C. David Allis, Lijuan Feng, Benjamin A. Nacev, Alborz Mahdavi, Jianjiong Gao, Alexey A. Soshnev, Nikolaus Schultz and Ritika Kundra. Their work appears in journals such as Journal of the American Chemical Society, Nature, Nature Communications, Cell and Nature Chemical 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.