Britta Swebilius Singer
- Aging top 2%
- Genetics top 2%
- Bacterial Genetics and Biotechnology 10
- Molecular Biology top 5%
- RNA and protein synthesis mechanisms 12
- Glycosylation and Glycoproteins Research 2
- Protein Structure and Dynamics 2
- CRISPR and Genetic Engineering 2
- Muscle Physiology and Disorders 2
- Ecology top 5%
- Bacteriophages and microbial interactions 14
- Rheumatology top 5%
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- Advanced Proteomics Techniques and Applications 4
- Co-authors
- Larry GoldDavid PribnowSidney T. ShinedlingThomas D. SchneiderGary D. StormoTimur ShtatlandDavid BrownCarolyn A. Napoli
- Cited by
- AgingGeneticsMolecular Biology
- Journals
- Cell (2 papers)Proceedings of the National Academy of Sciences (2 papers)Nucleic Acids Research (2 papers)
- Partner nations
- United StatesNorwayFrance
In The Last Decade
Britta Swebilius Singer
23 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Aging 110
- Genetics 814
- Molecular Biology 2.0k
- Ecology 509
- Rheumatology 190
Countries citing papers authored by Britta Swebilius Singer
This map shows the geographic impact of Britta Swebilius Singer'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 Britta Swebilius Singer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Britta Swebilius Singer more than expected).
Fields of papers citing papers by Britta Swebilius Singer
This network shows the impact of papers produced by Britta Swebilius Singer. 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 Britta Swebilius Singer. The network helps show where Britta Swebilius Singer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Britta Swebilius Singer, 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 | 2015 | 94 | |
| 2 | Growth Differentiation Factor 11 Is a Circulating Factor that Reverses Age-Related Cardiac Hypertrophybreakdown → | 2013 | 699 |
| 3 | 2008 | 63 | |
| 4 | 2002 | 30 | |
| 5 | 1997 | 107 | |
| 6 | 1997 | 24 | |
| 7 | 1997 | 106 | |
| 8 | 1993 | 46 | |
| 9 | 1991 | 15 | |
| 10 | 1990 | 22 | |
| 11 | 1988 | 71 | |
| 12 | 1988 | 9 | |
| 13 | 1987 | 24 | |
| 14 | 1984 | 15 | |
| 15 | 1982 | 124 | |
| 16 | 1981 | 17 | |
| 17 | 1981 | 145 | |
| 18 | 1981 | 57 | |
| 19 | 1981 | 57 | |
| 20 | 1976 | 37 |
About Britta Swebilius Singer
Britta Swebilius Singer is a scholar working on Ecology, Genetics and Molecular Biology, having authored 23 papers that have together received 2.5k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (14 papers), RNA and protein synthesis mechanisms (12 papers), Bacterial Genetics and Biotechnology (10 papers), Advanced Proteomics Techniques and Applications (4 papers), Glycosylation and Glycoproteins Research (2 papers), Protein Structure and Dynamics (2 papers), CRISPR and Genetic Engineering (2 papers) and Muscle Physiology and Disorders (2 papers). The work is most often cited by research in Aging (110 citations), Genetics (814 citations) and Molecular Biology (2.0k citations). Britta Swebilius Singer has collaborated with scholars based in United States, Norway and France. Frequent co-authors include Larry Gold, David Pribnow, Sidney T. Shinedling, Thomas D. Schneider, Gary D. Stormo, Timur Shtatland, David Brown, Carolyn A. Napoli, Amy J. Wagers and Jennifer L. Shadrach. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.
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.