David Damerell
Impact in
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- Glycosylation and Glycoproteins Research
- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- Protein Degradation and Inhibitors
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- Genetic Associations and Epidemiology
Papers in
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- Glycosylation and Glycoproteins Research 4
- Protein Structure and Dynamics 3
- Bioinformatics and Genomic Networks 2
- Ubiquitin and proteasome pathways 1
- vaccines and immunoinformatics approaches 1
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- thermodynamics and calorimetric analyses 1
- Co-authors
- Susan R. Jones (1 shared paper)Christopher R. Reynolds (1 shared paper)René Ranzinger (3 shared papers)Stuart M. Haslam (3 shared papers)Alessio Ceroni (2 shared papers)Anne Dell (2 shared papers)Kai Maaß (2 shared papers)Brian D. Marsden (2 shared papers)
- Journals
- Bioinformatics (3 papers)BMC Bioinformatics (1 paper)Glycobiology (1 paper)mAbs (1 paper)Nature Genetics (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
David Damerell
10 papers receiving 761 citations
Peers
Comparison fields: 5 of 69
- Molecular Biology 494
- Genetics 98
- Computational Theory and Mathematics 46
- Spectroscopy 42
- Organic Chemistry 51
Countries citing papers authored by David Damerell
This map shows the geographic impact of David Damerell'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 David Damerell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Damerell more than expected).
Fields of papers citing papers by David Damerell
This network shows the impact of papers produced by David Damerell. 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 David Damerell. The network helps show where David Damerell may publish in the future.
Co-authors
The 25 scholars most cited alongside David Damerell, 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 | 2008 | 166 | |
| 2 | 2019 | 151 | |
| 3 | 2012 | 142 | |
| 4 | 2010 | 107 | |
| 5 | 2014 | 73 | |
| 6 | 2018 | 59 | |
| 7 | 2015 | 54 | |
| 8 | 2020 | 19 | |
| 9 | 2023 | 5 | |
| 10 | 2025 | 5 |
About David Damerell
David Damerell is a scholar working on Molecular Biology, Physical and Theoretical Chemistry, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 10 papers that have together received 781 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (4 papers), Protein Structure and Dynamics (3 papers), Bioinformatics and Genomic Networks (2 papers), Ubiquitin and proteasome pathways (1 paper), Data Visualization and Analytics (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper), thermodynamics and calorimetric analyses (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Molecular Biology (494 citations), Genetics (98 citations), Computational Theory and Mathematics (46 citations), Spectroscopy (42 citations) and Organic Chemistry (51 citations). David Damerell has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Susan R. Jones, Christopher R. Reynolds, René Ranzinger, Stuart M. Haslam, Alessio Ceroni, Anne Dell, Kai Maaß, Brian D. Marsden, Lihua Liu and Yufeng Tong. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, Glycobiology, mAbs and Nature Genetics.
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.