David C. Dalgarno
- Molecular Biology top 5%
- Oncology top 5%
- Hematology top 2%
- Genetics top 2%
- Organic Chemistry top 5%
- Co-authors
- Barry A. LevineHongtao YuJames ChenSibo FengAndrew W. BrauerRobert J. P. WilliamsWilliam C. ShakespeareTomi K. Sawyer
- Topics
- Protein Kinase Regulation and GTPase Signaling (18 papers)RNA and protein synthesis mechanisms (8 papers)Chemical Synthesis and Analysis (8 papers)
- Cited by
- HematologyGeneticsMolecular Biology
- Journals
- CellProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesUnited KingdomPoland
In The Last Decade
David C. Dalgarno
71 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Molecular Biology 2.4k
- Oncology 828
- Hematology 557
- Genetics 377
- Organic Chemistry 353
Countries citing papers authored by David C. Dalgarno
This map shows the geographic impact of David C. Dalgarno'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 C. Dalgarno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David C. Dalgarno more than expected).
Fields of papers citing papers by David C. Dalgarno
This network shows the impact of papers produced by David C. Dalgarno. 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 C. Dalgarno. The network helps show where David C. Dalgarno may publish in the future.
Co-authorship network of co-authors of David C. Dalgarno
This figure shows the co-authorship network connecting the top 25 collaborators of David C. Dalgarno. A scholar is included among the top collaborators of David C. Dalgarno 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 David C. Dalgarno. David C. Dalgarno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | High-throughput prediction of protein conformational distributions with subsampled AlphaFold2breakdown → | 75 |
| 3 | 4 | |
| 4 | 18 | |
| 5 | 23 | |
| 6 | 68 | |
| 7 | 65 | |
| 8 | Structure-based design of AP23573, a phosphorus-containing analog of rapamycin for anti-tumor therapy. | 19 |
| 9 | 10 | |
| 10 | 14 | |
| 11 | 42 | |
| 12 | 30 | |
| 13 | 16 | |
| 14 | 7 | |
| 15 | 23 | |
| 16 | 144 | |
| 17 | Structural basis for the binding of proline-rich peptides to SH3 domainsbreakdown → | 880 |
| 18 | 19 | |
| 19 | 20 | |
| 20 | 64 |
About David C. Dalgarno
David C. Dalgarno is a scholar working on Hematology, Oncology and Biophysics, having authored 71 papers that have together received 3.6k indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (18 papers), RNA and protein synthesis mechanisms (8 papers) and Chemical Synthesis and Analysis (8 papers). The work is most often cited by research in Hematology (557 citations), Genetics (377 citations) and Molecular Biology (2.4k citations). David C. Dalgarno has collaborated with scholars based in United States, United Kingdom and Poland. Frequent co-authors include Barry A. Levine, Hongtao Yu, James Chen, Sibo Feng, Andrew W. Brauer, Robert J. P. Williams, William C. Shakespeare, Tomi K. Sawyer, Yihan Wang and Tim Clackson. 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.