Daniel E. Todd
Impact in
- Endocrinology top 10%
-
- Bacterial biofilms and quorum sensing
- Melanoma and MAPK Pathways
- Cell death mechanisms and regulation
- Protein Kinase Regulation and GTPase Signaling
Papers in
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- Melanoma and MAPK Pathways 6
- Cell death mechanisms and regulation 4
- Protein Kinase Regulation and GTPase Signaling 3
- Ubiquitin and proteasome pathways 2
- Bacterial biofilms and quorum sensing 2
- Signaling Pathways in Disease 1
- Oncology 4
- Cancer-related Molecular Pathways 4
- Co-authors
- Simon J. Cook (6 shared papers)Neil A. Whitehead (2 shared papers)George P. C. Salmond (2 shared papers)Martin Welch (2 shared papers)Simon J. McGowan (2 shared papers)Barrie W. Bycroft (1 shared paper)Kathryn Balmanno (4 shared papers)Sarah A Molton (3 shared papers)
- Journals
- Oncogene (3 papers)Cellular Signalling (2 papers)Journal of Computer-Aided Molecular Design (1 paper)Journal of Medicinal Chemistry (1 paper)Biochemical Society Transactions (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Daniel E. Todd
10 papers receiving 542 citations
Peers
Comparison fields: 5 of 81
- Endocrinology 32
- Molecular Biology 396
- Molecular Medicine 28
- Genetics 118
- Oncology 76
Countries citing papers authored by Daniel E. Todd
This map shows the geographic impact of Daniel E. Todd'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 Daniel E. Todd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel E. Todd more than expected).
Fields of papers citing papers by Daniel E. Todd
This network shows the impact of papers produced by Daniel E. Todd. 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 Daniel E. Todd. The network helps show where Daniel E. Todd may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel E. Todd, 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 | 2000 | 162 | |
| 2 | 2004 | 79 | |
| 3 | 2013 | 70 | |
| 4 | 2004 | 68 | |
| 5 | 2002 | 47 | |
| 6 | 2003 | 45 | |
| 7 | 2000 | 36 | |
| 8 | 2011 | 27 | |
| 9 | 2008 | 18 | |
| 10 | 2005 | 3 |
About Daniel E. Todd
Daniel E. Todd is a scholar working on Molecular Biology, Oncology, Genetics, Cellular and Molecular Neuroscience and Virology, having authored 10 papers that have together received 555 indexed citations. Recurring topics across this work include Melanoma and MAPK Pathways (6 papers), Cell death mechanisms and regulation (4 papers), Cancer-related Molecular Pathways (4 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Ubiquitin and proteasome pathways (2 papers), Bacterial Genetics and Biotechnology (2 papers), Bacterial biofilms and quorum sensing (2 papers) and Signaling Pathways in Disease (1 paper). The work is most often cited by research in Endocrinology (32 citations), Molecular Biology (396 citations), Molecular Medicine (28 citations), Genetics (118 citations) and Oncology (76 citations). Daniel E. Todd has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Simon J. Cook, Neil A. Whitehead, George P. C. Salmond, Martin Welch, Simon J. McGowan, Barrie W. Bycroft, Kathryn Balmanno, Sarah A Molton, Claire R. Weston and Andrew P. Garner. Their work appears in journals such as Oncogene, Cellular Signalling, Journal of Computer-Aided Molecular Design, Journal of Medicinal Chemistry and Biochemical Society Transactions.
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.