Glenn J. Myatt
- Molecular Biology
- Computational Theory and Mathematics top 1%
- Cardiology and Cardiovascular Medicine top 10%
- Organic Chemistry
- Cellular and Molecular Neuroscience
- Co-authors
- Valerie J. GilletA. Peter JohnsonJoseph S. VerducciKevin P. CrossZsolt ZsoldosPaul E. BlowerCarlos A. Obejero‐PazJames Kramer
- Topics
- Computational Drug Discovery Methods (14 papers)Animal testing and alternatives (6 papers)Effects and risks of endocrine disrupting chemicals (4 papers)
- Cited by
- Computational Theory and MathematicsChemical Health and SafetyCardiology and Cardiovascular Medicine
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Glenn J. Myatt
33 papers receiving 930 citations
Peers
Comparison fields: 5 of 142
- Molecular Biology 489
- Computational Theory and Mathematics 421
- Cardiology and Cardiovascular Medicine 234
- Organic Chemistry 92
- Cellular and Molecular Neuroscience 89
Countries citing papers authored by Glenn J. Myatt
This map shows the geographic impact of Glenn J. Myatt'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 Glenn J. Myatt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Glenn J. Myatt more than expected).
Fields of papers citing papers by Glenn J. Myatt
This network shows the impact of papers produced by Glenn J. Myatt. 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 Glenn J. Myatt. The network helps show where Glenn J. Myatt may publish in the future.
Co-authorship network of co-authors of Glenn J. Myatt
This figure shows the co-authorship network connecting the top 25 collaborators of Glenn J. Myatt. A scholar is included among the top collaborators of Glenn J. Myatt 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 Glenn J. Myatt. Glenn J. Myatt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 19 | |
| 5 | 3 | |
| 6 | 10 | |
| 7 | 20 | |
| 8 | 10 | |
| 9 | 5 | |
| 10 | 18 | |
| 11 | 24 | |
| 12 | 255 | |
| 13 | A practical guide to data visualization, advanced data mining methods, and applications | 3 |
| 14 | A practical guide to exploratory data analysis and data mining | 3 |
| 15 | 6 | |
| 16 | 39 | |
| 17 | 17 | |
| 18 | 117 | |
| 19 | 31 | |
| 20 | 120 |
About Glenn J. Myatt
Glenn J. Myatt is a scholar working on Chemical Health and Safety, Computational Theory and Mathematics and Small Animals, having authored 36 papers that have together received 1.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (14 papers), Animal testing and alternatives (6 papers) and Effects and risks of endocrine disrupting chemicals (4 papers). The work is most often cited by research in Computational Theory and Mathematics (421 citations), Chemical Health and Safety (9 citations) and Cardiology and Cardiovascular Medicine (234 citations). Glenn J. Myatt has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Valerie J. Gillet, A. Peter Johnson, Joseph S. Verducci, Kevin P. Cross, Zsolt Zsoldos, Paul E. Blower, Carlos A. Obejero‐Paz, James Kramer, Andrew Bruening‐Wright and Yuri A. Kuryshev. Their work appears in journals such as Scientific Reports, Journal of Medicinal Chemistry and Frontiers in Pharmacology.
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.