William S. Moore
- Genetics top 0.2%
- Ecology, Evolution, Behavior and Systematics top 0.2%
- Ecology top 0.5%
- Molecular Biology top 5%
- Nature and Landscape Conservation top 1%
- Co-authors
- Kathleen J. MigliaJohn HarshmanEdward L. BraunChristopher J. HuddlestonSushma ReddyChristopher C. WittRebecca T. KimballTamaki Yuri
- Topics
- Genetic diversity and population structure (37 papers)Plant and animal studies (19 papers)Genomics and Phylogenetic Studies (15 papers)
- Journals
- ScienceProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
William S. Moore
138 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Genetics 3.2k
- Ecology, Evolution, Behavior and Systematics 2.2k
- Ecology 2.0k
- Molecular Biology 1.8k
- Nature and Landscape Conservation 1.4k
Countries citing papers authored by William S. Moore
This map shows the geographic impact of William S. Moore'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 William S. Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William S. Moore more than expected).
Fields of papers citing papers by William S. Moore
This network shows the impact of papers produced by William S. Moore. 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 William S. Moore. The network helps show where William S. Moore may publish in the future.
Co-authorship network of co-authors of William S. Moore
This figure shows the co-authorship network connecting the top 25 collaborators of William S. Moore. A scholar is included among the top collaborators of William S. Moore 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 William S. Moore. William S. Moore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 202 | |
| 4 | 2 | |
| 5 | 24 | |
| 6 | 24 | |
| 7 | 26 | |
| 8 | 58 | |
| 9 | 72 | |
| 10 | 12 | |
| 11 | Income Inequality and Industrial Composition | 4 |
| 12 | 5 | |
| 13 | 1 | |
| 14 | 63 | |
| 15 | A molecular phylogenetic study of the Old World treefrog family Rhacophoridae | 55 |
| 16 | 250 | |
| 17 | 2 | |
| 18 | The Learning Environment Preferences: Exploring the Construct Validity of an Objective Measure of the Perry Scheme of Intellectual Development. | 66 |
| 19 | 18 | |
| 20 | 28 |
About William S. Moore
William S. Moore is a scholar working on Oral Surgery, Genetics and General Dentistry, having authored 144 papers that have together received 7.4k indexed citations. Recurring topics across this work include Genetic diversity and population structure (37 papers), Plant and animal studies (19 papers) and Genomics and Phylogenetic Studies (15 papers). The work is most often cited by research in Paleontology (1.3k citations), Ecological Modeling (538 citations) and Genetics (3.2k citations). William S. Moore has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Kathleen J. Miglia, John Harshman, Edward L. Braun, Christopher J. Huddleston, Sushma Reddy, Christopher C. Witt, Rebecca T. Kimball, Tamaki Yuri, Shannon J. Hackett and Frederick H. Sheldon. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.