Nansie A. McHugh
- Molecular Biology
- Physiology
- Computational Theory and Mathematics top 10%
- Pharmacology
- Cardiology and Cardiovascular Medicine
- Co-authors
- Gary F. MerrillSaul R. PowellJason SchairerEric M. ParkerYunsheng HsiehWalter A. KorfmacherJiwen ChenCorey Strickland
- Topics
- Computational Drug Discovery Methods (4 papers)Alzheimer's disease research and treatments (3 papers)Menopause: Health Impacts and Treatments (3 papers)
- Journals
- The FASEB JournalJournal of Applied PhysiologyJournal of Pharmacology and Experimental Therapeutics
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Nansie A. McHugh
15 papers receiving 306 citations
Peers
Comparison fields: 5 of 67
- Molecular Biology 101
- Physiology 96
- Computational Theory and Mathematics 63
- Pharmacology 55
- Cardiology and Cardiovascular Medicine 44
Countries citing papers authored by Nansie A. McHugh
This map shows the geographic impact of Nansie A. McHugh'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 Nansie A. McHugh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nansie A. McHugh more than expected).
Fields of papers citing papers by Nansie A. McHugh
This network shows the impact of papers produced by Nansie A. McHugh. 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 Nansie A. McHugh. The network helps show where Nansie A. McHugh may publish in the future.
Co-authorship network of co-authors of Nansie A. McHugh
This figure shows the co-authorship network connecting the top 25 collaborators of Nansie A. McHugh. A scholar is included among the top collaborators of Nansie A. McHugh 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 Nansie A. McHugh. Nansie A. McHugh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 5 | |
| 3 | 49 | |
| 4 | 17 | |
| 5 | 3 | |
| 6 | 50 | |
| 7 | 33 | |
| 8 | 32 | |
| 9 | 10 | |
| 10 | 2 | |
| 11 | 8 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 39 | |
| 15 | 50 |
About Nansie A. McHugh
Nansie A. McHugh is a scholar working on Computational Theory and Mathematics, Orthopedics and Sports Medicine and Sensory Systems, having authored 15 papers that have together received 318 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Alzheimer's disease research and treatments (3 papers) and Menopause: Health Impacts and Treatments (3 papers). The work is most often cited by research in Computational Theory and Mathematics (63 citations), Physiology (96 citations) and Pharmacology (55 citations). Nansie A. McHugh has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Gary F. Merrill, Saul R. Powell, Jason Schairer, Eric M. Parker, Yunsheng Hsieh, Walter A. Korfmacher, Jiwen Chen, Corey Strickland, Matthew Kennedy and Leonard Favreau. Their work appears in journals such as The FASEB Journal, Journal of Applied Physiology and Journal of Pharmacology and Experimental Therapeutics.
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.