Sean D. Taverna
- Molecular Biology top 2%
- Plant Science top 5%
- Oncology top 10%
- Genetics top 10%
- Immunology
- Co-authors
- C. David AllisHaitao LiDinshaw J. PatelAlexander J. RuthenburgAlan J. TackettRobert S. CoyneDonald F. HuntYifan Liu
- Topics
- Genomics and Chromatin Dynamics (28 papers)Epigenetics and DNA Methylation (23 papers)Cancer-related gene regulation (10 papers)
- Cited by
- Molecular BiologyAgingPlant Science
- Journals
- CellProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesChinaCanada
In The Last Decade
Sean D. Taverna
43 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Molecular Biology 3.2k
- Plant Science 540
- Oncology 240
- Genetics 222
- Immunology 211
Countries citing papers authored by Sean D. Taverna
This map shows the geographic impact of Sean D. Taverna'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 Sean D. Taverna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sean D. Taverna more than expected).
Fields of papers citing papers by Sean D. Taverna
This network shows the impact of papers produced by Sean D. Taverna. 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 Sean D. Taverna. The network helps show where Sean D. Taverna may publish in the future.
Co-authorship network of co-authors of Sean D. Taverna
This figure shows the co-authorship network connecting the top 25 collaborators of Sean D. Taverna. A scholar is included among the top collaborators of Sean D. Taverna based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sean D. Taverna. Sean D. Taverna is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 52 | |
| 5 | 32 | |
| 6 | 38 | |
| 7 | 52 | |
| 8 | 5 | |
| 9 | 11 | |
| 10 | 67 | |
| 11 | 47 | |
| 12 | 83 | |
| 13 | 83 | |
| 14 | 7 | |
| 15 | 11 | |
| 16 | 12 | |
| 17 | 26 | |
| 18 | How chromatin-binding modules interpret histone modifications: lessons from professional pocket pickersbreakdown → | 1102 |
| 19 | 256 | |
| 20 | 86 |
About Sean D. Taverna
Sean D. Taverna is a scholar working on Molecular Biology, Physiology and Anesthesiology and Pain Medicine, having authored 45 papers that have together received 3.6k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (28 papers), Epigenetics and DNA Methylation (23 papers) and Cancer-related gene regulation (10 papers). The work is most often cited by research in Molecular Biology (3.2k citations), Aging (40 citations) and Plant Science (540 citations). Sean D. Taverna has collaborated with scholars based in United States, China and Canada. Frequent co-authors include C. David Allis, Haitao Li, Dinshaw J. Patel, Alexander J. Ruthenburg, Alan J. Tackett, Robert S. Coyne, Donald F. Hunt, Yifan Liu, Jeffrey Shabanowitz and Jin Li. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.