Michael Keehan
- Genetics top 5%
- Genetic and phenotypic traits in livestock 16
- Genetic Mapping and Diversity in Plants and Animals 8
- Animal Genetics and Reproduction 3
- Agronomy and Crop Science top 5%
- Milk Quality and Mastitis in Dairy Cows 2
- Reproductive Physiology in Livestock 2
- Cancer Research top 10%
- Cancer-related molecular mechanisms research 4
- Animal Science and Zoology top 10%
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- Wheat and Barley Genetics and Pathology 2
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- melanin and skin pigmentation 2
Michael Keehan
18 papers receiving 687 citations
Peers
Comparison fields: 5 of 46
- Genetics 634
- Agronomy and Crop Science 136
- Cancer Research 197
- Animal Science and Zoology 52
- Plant Science 120
Countries citing papers authored by Michael Keehan
This map shows the geographic impact of Michael Keehan'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 Michael Keehan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Keehan more than expected).
Fields of papers citing papers by Michael Keehan
This network shows the impact of papers produced by Michael Keehan. 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 Michael Keehan. The network helps show where Michael Keehan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Keehan, 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 | 2023 | 1 | |
| 2 | 2022 | 9 | |
| 3 | 2021 | 22 | |
| 4 | 2019 | 20 | |
| 5 | 2019 | 22 | |
| 6 | 2018 | 8 | |
| 7 | 2017 | 45 | |
| 8 | 2017 | 14 | |
| 9 | 2017 | 14 | |
| 10 | 2016 | 91 | |
| 11 | 2016 | 58 | |
| 12 | NGS-based reverse genetic screen reveals loss-of-function variants compromising fertility in cattle | 2014 | 3 |
| 13 | 2011 | 255 | |
| 14 | Application of genomic selection in the New Zealand dairy cattle industry. | 2010 | 14 |
| 15 | 2009 | 22 | |
| 16 | 2009 | 10 | |
| 17 | 2009 | 88 | |
| 18 | Application of genomic information in a dairy cattle breeding scheme. | 2007 | 1 |
About Michael Keehan
Michael Keehan is a scholar working on Genetics, Cancer Research and Agronomy and Crop Science, having authored 18 papers that have together received 697 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (16 papers), Genetic Mapping and Diversity in Plants and Animals (8 papers), Cancer-related molecular mechanisms research (4 papers), Animal Genetics and Reproduction (3 papers), Milk Quality and Mastitis in Dairy Cows (2 papers), Wheat and Barley Genetics and Pathology (2 papers), melanin and skin pigmentation (2 papers) and Reproductive Physiology in Livestock (2 papers). The work is most often cited by research in Genetics (634 citations), Agronomy and Crop Science (136 citations) and Cancer Research (197 citations). Michael Keehan has collaborated with scholars based in New Zealand, Belgium and China. Frequent co-authors include Richard Spelman, Mathew D. Littlejohn, Wouter Coppieters, J. Arias, Stephen R. Davis, B.L. Harris, Michel Georges, Thomas Johnson, Tom Druet and Latifa Karim. Their work appears in journals such as Journal of Dairy Science, Animal Genetics, Genetics Selection Evolution, Nature Genetics and BMC Genomics.
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.