Daniel E. Todd

629 citations
10 papers · 513 · h-index 9

Impact in

    • Bacterial biofilms and quorum sensing
    • Melanoma and MAPK Pathways
    • Cell death mechanisms and regulation
    • Protein Kinase Regulation and GTPase Signaling

Papers in

    • Melanoma and MAPK Pathways 6
    • Cell death mechanisms and regulation 4
    • Protein Kinase Regulation and GTPase Signaling 3
    • Bacterial biofilms and quorum sensing 2
    • Ubiquitin and proteasome pathways 2
    • Signaling Pathways in Disease 1
    • Cancer-related Molecular Pathways 4

Daniel E. Todd

10 papers receiving 501 citations

Peers

Daniel E. Todd
Comparison fields: 5 of 82
  • Endocrinology 30
  • Molecular Biology 381
  • Molecular Medicine 27
  • Genetics 103
  • Oncology 75
Replace Keith S. Wong with:
Keith S. Wong Canada
Yoshio Shibagaki Japan
Saku Miyamoto Japan
M. Christine Bruce Canada
Anthony Arnoldo Canada
Jan Félix France
Dev Mangroo Canada
Kristin T. Chun United States
Xin Bi United States
Corinne Lafon France
Daniel E. Todd relative to Keith S. Wong Canada Keith S. Wong's profile →
Citations per field
00.5×1.6×
Keith S. Wong · 1×
Citations per year

Countries citing papers authored by Daniel E. Todd

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Daniel E. Todd Line = papers co-authored together Daniel E. Todd links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2000149
2 200474
3 201366
4 200461
5 200245
6 200344
7 200027
8 201126
9 200818
10 20053

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 513 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), Bacterial biofilms and quorum sensing (2 papers), Bacterial Genetics and Biotechnology (2 papers), Ubiquitin and proteasome pathways (2 papers) and Signaling Pathways in Disease (1 paper). The work is most often cited by research in Endocrinology (30 citations), Molecular Biology (381 citations), Molecular Medicine (27 citations), Genetics (103 citations) and Oncology (75 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, Martin Welch, George P. C. Salmond, Simon J. McGowan, Kathryn Balmanno, Barrie W. Bycroft, Sarah A Molton, Andrew P. Garner and Claire R. Weston. Their work appears in journals such as Oncogene, Cellular Signalling, Molecular Microbiology, The EMBO Journal and Journal of Medicinal Chemistry.

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.

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