John M. Hickey
- Genetics top 0.2%
- Plant Science top 0.5%
- Molecular Biology
- Agronomy and Crop Science top 1%
- Animal Science and Zoology top 2%
- Co-authors
- Gregor GorjancGustavo de los CamposHans D. DaetwylerRicardo Pong‐WongM.P.L. CalusR. Chris GaynorMatthew A. ClevelandJosé Crossa
- Topics
- Genetic and phenotypic traits in livestock (73 papers)Genetic Mapping and Diversity in Plants and Animals (69 papers)Genetics and Plant Breeding (41 papers)
- Journals
- Nature GeneticsSHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- United KingdomAustraliaSweden
In The Last Decade
John M. Hickey
94 papers receiving 5.0k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Genetics 4.2k
- Plant Science 3.1k
- Molecular Biology 490
- Agronomy and Crop Science 434
- Animal Science and Zoology 300
Countries citing papers authored by John M. Hickey
This map shows the geographic impact of John M. Hickey'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 John M. Hickey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John M. Hickey more than expected).
Fields of papers citing papers by John M. Hickey
This network shows the impact of papers produced by John M. Hickey. 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 John M. Hickey. The network helps show where John M. Hickey may publish in the future.
Co-authorship network of co-authors of John M. Hickey
This figure shows the co-authorship network connecting the top 25 collaborators of John M. Hickey. A scholar is included among the top collaborators of John M. Hickey 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 John M. Hickey. John M. Hickey 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 | 7 | |
| 3 | 6 | |
| 4 | 8 | |
| 5 | 127 | |
| 6 | 12 | |
| 7 | 55 | |
| 8 | 19 | |
| 9 | 39 | |
| 10 | 33 | |
| 11 | 23 | |
| 12 | 23 | |
| 13 | 103 | |
| 14 | Selection of appropriate genomic selection model in an unstructured germplasm set of peanut (Arachis hypogaea L.) | 1 |
| 15 | Use of Genome Editing in Animal Breeding Programs | 0 |
| 16 | Hierarchical Quantitative Genetic Model Using Genomic Information | 1 |
| 17 | Sequencing Millions of Animals for Genomic Selection 2.0 | 7 |
| 18 | Selection on Recombination Rate to Increase Genetic Gain | 2 |
| 19 | 62 | |
| 20 | Reliability of breeding values in selected populations. | 1 |
About John M. Hickey
John M. Hickey is a scholar working on Genetics, Plant Science and Horticulture, having authored 96 papers that have together received 5.1k indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (73 papers), Genetic Mapping and Diversity in Plants and Animals (69 papers) and Genetics and Plant Breeding (41 papers). The work is most often cited by research in Genetics (4.2k citations), Plant Science (3.1k citations) and Agronomy and Crop Science (434 citations). John M. Hickey has collaborated with scholars based in United Kingdom, Australia and Sweden. Frequent co-authors include Gregor Gorjanc, Gustavo de los Campos, Hans D. Daetwyler, Ricardo Pong‐Wong, M.P.L. Calus, R. Chris Gaynor, Matthew A. Cleveland, José Crossa, Raman Babu and Ian Mackay. Their work appears in journals such as Nature Genetics, SHILAP Revista de lepidopterología and Bioinformatics.
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.