K MacPhee-Quigley
Impact in
- Pharmacology top 1%
- Cholinesterase and Neurodegenerative Diseases
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- Computational Drug Discovery Methods
Papers in ⓘ
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- Computational Drug Discovery Methods 8
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- Cholinesterase and Neurodegenerative Diseases 8
- Co-authors
- Palmer Taylor (7 shared papers)Susan S. Taylor (6 shared papers)Shelley Camp (3 shared papers)Theodore Friedmann (3 shared papers)Mark Schumacher (3 shared papers)Gretchen Gibney (3 shared papers)Yves Maulet (2 shared papers)Michael Newton (2 shared papers)
- Journals
- Journal of Biological Chemistry (3 papers)Biochemistry (1 paper)Nature (1 paper)Proceedings of the National Academy of Sciences (1 paper)Trends in Neurosciences (1 paper)
- Partner nations
- United States
In The Last Decade
K MacPhee-Quigley
8 papers receiving 916 citations
Peers
Comparison fields: 5 of 67
- Pharmacology 698
- Computational Theory and Mathematics 447
- Complementary and alternative medicine 62
- Molecular Biology 506
- Insect Science 60
Countries citing papers authored by K MacPhee-Quigley
This map shows the geographic impact of K MacPhee-Quigley'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 K MacPhee-Quigley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K MacPhee-Quigley more than expected).
Fields of papers citing papers by K MacPhee-Quigley
This network shows the impact of papers produced by K MacPhee-Quigley. 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 K MacPhee-Quigley. The network helps show where K MacPhee-Quigley may publish in the future.
Co-authors
The 15 scholars most cited alongside K MacPhee-Quigley, 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 | 1986 | 364 | |
| 2 | 1992 | 118 | |
| 3 | 1986 | 117 | |
| 4 | 1990 | 111 | |
| 5 | 1985 | 106 | |
| 6 | 1988 | 71 | |
| 7 | 1987 | 32 | |
| 8 | Primary structure of acetylcholinesterase: implications for regulation and function. | 1986 | 15 |
About K MacPhee-Quigley
K MacPhee-Quigley is a scholar working on Computational Theory and Mathematics, Pharmacology, Molecular Biology, Spectroscopy and Organic Chemistry, having authored 8 papers that have together received 934 indexed citations. Recurring topics across this work include Cholinesterase and Neurodegenerative Diseases (8 papers), Computational Drug Discovery Methods (8 papers), Enzyme function and inhibition (4 papers), bioluminescence and chemiluminescence research (2 papers), Molecular spectroscopy and chirality (1 paper) and Chemical Reaction Mechanisms (1 paper). The work is most often cited by research in Pharmacology (698 citations), Computational Theory and Mathematics (447 citations), Complementary and alternative medicine (62 citations), Molecular Biology (506 citations) and Insect Science (60 citations). K MacPhee-Quigley has collaborated with scholars based in United States. Frequent co-authors include Palmer Taylor, Susan S. Taylor, Shelley Camp, Theodore Friedmann, Mark Schumacher, Gretchen Gibney, Yves Maulet, Michael Newton, Thomas S. Vedvick and Marc Dionne. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry, Nature, Proceedings of the National Academy of Sciences and Trends in Neurosciences.
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.