Will Hayes
Impact in
- Software top 5%
- Software Reliability and Analysis Research
- Endocrinology top 5%
Papers in
- Genetics 11
- Bacterial Genetics and Biotechnology 8
- Evolution and Genetic Dynamics 6
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- DNA Repair Mechanisms 2
- Photosynthetic Processes and Mechanisms 2
- Co-authors
- Dennis R. Goldenson (1 shared paper)David Zubrow (1 shared paper)Mark C. Paulk (1 shared paper)James D. Herbsleb (1 shared paper)F Jacob (1 shared paper)E. Wollman (1 shared paper)K. A. Stacey (2 shared papers)James D. Watson (1 shared paper)
- Journals
- Genetics Research (3 papers)Cold Spring Harbor Symposia on Quantitative Biology (2 papers)Nature (2 papers)British Medical Bulletin (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Will Hayes
26 papers receiving 904 citations
Peers
Comparison fields: 5 of 117
- Software 74
- Endocrinology 78
- Management Information Systems 129
- Molecular Medicine 60
- Information Systems 275
Countries citing papers authored by Will Hayes
This map shows the geographic impact of Will Hayes'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 Will Hayes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Hayes more than expected).
Fields of papers citing papers by Will Hayes
This network shows the impact of papers produced by Will Hayes. 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 Will Hayes. The network helps show where Will Hayes may publish in the future.
Co-authors
The 20 scholars most cited alongside Will Hayes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 284 | |
| 2 | 1953 | 147 | |
| 3 | 1956 | 146 | |
| 4 | 1953 | 120 | |
| 5 | 1957 | 76 | |
| 6 | 1952 | 61 | |
| 7 | 2003 | 46 | |
| 8 | 1972 | 37 | |
| 9 | 1952 | 27 | |
| 10 | 1969 | 24 | |
| 11 | 1961 | 19 | |
| 12 | 2000 | 18 | |
| 13 | 1961 | 16 | |
| 14 | 1953 | 12 | |
| 15 | 1962 | 10 | |
| 16 | 1966 | 8 | |
| 17 | 2005 | 7 | |
| 18 | 2014 | 5 | |
| 19 | 2002 | 4 | |
| 20 | 1969 | 4 |
About Will Hayes
Will Hayes is a scholar working on Genetics, Molecular Biology, Information Systems, Software and Ecology, having authored 27 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (8 papers), Evolution and Genetic Dynamics (6 papers), Software Reliability and Analysis Research (6 papers), Software Engineering Techniques and Practices (5 papers), Software Engineering Research (4 papers), Bacteriophages and microbial interactions (3 papers), DNA Repair Mechanisms (2 papers) and Photosynthetic Processes and Mechanisms (2 papers). The work is most often cited by research in Software (74 citations), Endocrinology (78 citations), Management Information Systems (129 citations), Molecular Medicine (60 citations) and Information Systems (275 citations). Will Hayes has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Dennis R. Goldenson, David Zubrow, Mark C. Paulk, James D. Herbsleb, F Jacob, E. Wollman, K. A. Stacey, James D. Watson, Fiona R. Saunders and Felicia Schanche Hodge. Their work appears in journals such as Genetics Research, Cold Spring Harbor Symposia on Quantitative Biology, Nature, British Medical Bulletin and Proceedings of the National Academy of Sciences.
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.