Suzanne J. Rowe

1.3k total citations
52 papers, 811 citations indexed

About

Suzanne J. Rowe is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, Suzanne J. Rowe has authored 52 papers receiving a total of 811 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Genetics, 23 papers in Agronomy and Crop Science and 12 papers in Animal Science and Zoology. Recurrent topics in Suzanne J. Rowe's work include Genetic and phenotypic traits in livestock (30 papers), Ruminant Nutrition and Digestive Physiology (23 papers) and Genetic Mapping and Diversity in Plants and Animals (13 papers). Suzanne J. Rowe is often cited by papers focused on Genetic and phenotypic traits in livestock (30 papers), Ruminant Nutrition and Digestive Physiology (23 papers) and Genetic Mapping and Diversity in Plants and Animals (13 papers). Suzanne J. Rowe collaborates with scholars based in New Zealand, United Kingdom and Denmark. Suzanne J. Rowe's co-authors include Dirk‐Jan de Koning, John C. McEwan, E.W. Lovrien, William G. Hill, Ian White, Santiago Avendaño, Mark H. Greene, Margaret A. Tucker, Lynn R. Goldin and Mary C. Fraser and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Suzanne J. Rowe

49 papers receiving 783 citations

Peers

Suzanne J. Rowe
Zhengrong Yuan China
Kerry Hull Canada
Maria Raquel Santos Carvalho Brazil
Stanisław Kamiński Poland
H. Michael Kubisch United States
Ran Zhao China
Petr Šimeček Czechia
Nima Rafati Sweden
A. Ruvinsky Russia
Fabio Marroni Italy
Zhengrong Yuan China
Suzanne J. Rowe
Citations per year, relative to Suzanne J. Rowe Suzanne J. Rowe (= 1×) peers Zhengrong Yuan

Countries citing papers authored by Suzanne J. Rowe

Since Specialization
Citations

This map shows the geographic impact of Suzanne J. Rowe'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 Suzanne J. Rowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suzanne J. Rowe more than expected).

Fields of papers citing papers by Suzanne J. Rowe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Suzanne J. Rowe. 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 Suzanne J. Rowe. The network helps show where Suzanne J. Rowe may publish in the future.

Co-authorship network of co-authors of Suzanne J. Rowe

This figure shows the co-authorship network connecting the top 25 collaborators of Suzanne J. Rowe. A scholar is included among the top collaborators of Suzanne J. Rowe 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 Suzanne J. Rowe. Suzanne J. Rowe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lambe, N.R., F. McGovern, E.A. Navajas, et al.. (2025). Comparison of country-specific predictions of feed intake and methane emissions in sheep using different proxies. Livestock Science. 296. 105716–105716.
2.
Alemu, Setegn Worku, Timothy P. Bilton, Patricia L. Johnson, et al.. (2025). Improving genomic prediction accuracy for methane emission and feed efficiency in sheep: integrating rumen microbial PCA with host genomic variation using neural network GBLUP (NN-GBLUP). Genetics Selection Evolution. 57(1). 41–41. 1 indexed citations
3.
McGovern, F., D.P. Berry, John C. McEwan, et al.. (2024). Comparison of greenhouse gas emissions from sheep measured using both respiration and portable accumulation chambers. animal. 18(5). 101140–101140. 1 indexed citations
4.
Johnson, Patricia L., et al.. (2023). Genetic parameter analysis of bareness and tail traits in New Zealand sheep. Journal of Animal Science. 101. 1 indexed citations
5.
Johnson, Patricia L., S. M. Hickey, Mélanie Hall, et al.. (2022). Genetic parameters for residual feed intake, methane emissions, and body composition in New Zealand maternal sheep. Frontiers in Genetics. 13. 911639–911639. 16 indexed citations
6.
Rowe, Suzanne J., S. M. Hickey, G. J. Greer, et al.. (2022). Can we have our steak and eat it: The impact of breeding for lowered environmental impact on yield and meat quality in sheep. Frontiers in Genetics. 13. 911355–911355. 3 indexed citations
7.
Hickey, S. M., W. E. Bain, Timothy P. Bilton, et al.. (2022). Impact of breeding for reduced methane emissions in New Zealand sheep on maternal and health traits. Frontiers in Genetics. 13. 910413–910413. 7 indexed citations
8.
Rowe, Suzanne J., Tracey C. van Stijn, Hannah Henry, et al.. (2020). A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling. PLoS ONE. 15(4). e0219882–e0219882. 20 indexed citations
9.
Bilton, Timothy P., John C. McEwan, Shannon Clarke, et al.. (2018). Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data. Genetics. 209(2). 389–400. 23 indexed citations
10.
Rowe, Suzanne J., Tracey C. van Stijn, Rüdiger Bräuning, et al.. (2018). High-throughput rumen microbial profiling using genotyping-by-sequencing. Proceedings of the World Congress on Genetics Applied to Livestock Production. 331. 2 indexed citations
11.
Jonker, Arjan, S. M. Hickey, John C. McEwan, et al.. (2018). Rumen characteristics and total tract digestibility in low and high methane yield selection line sheep offered fresh good or poor quality pasture. Proceedings of the World Congress on Genetics Applied to Livestock Production. 366. 4 indexed citations
12.
13.
Rowe, Suzanne J., et al.. (2014). Analysis of the genetics of boar taint reveals both single SNPs and regional effects. BMC Genomics. 15(1). 424–424. 23 indexed citations
14.
Deary, Ian J., Jian Yang, Gail Davies, et al.. (2012). Genetic contributions to stability and change in intelligence from childhood to old age. Nature. 482(7384). 212–215. 169 indexed citations
15.
Rowe, Suzanne J. & Albert Tenesa. (2012). Human Complex Trait Genetics: Lifting the Lid of the Genomics Toolbox - from Pathways to Prediction. Current Genomics. 13(3). 213–224. 7 indexed citations
16.
Jouffe, Vincent, Suzanne J. Rowe, Laurence Liaubet, et al.. (2009). Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs. BMC Proceedings. 3(S4). S14–S14. 7 indexed citations
17.
Rowe, Suzanne J., Ricardo Pong‐Wong, Chris Haley, Sara Knott, & Dirk‐Jan de Koning. (2008). Detecting dominant QTL with variance component analysis in simulated pedigrees. Genetics Research. 90(4). 363–374. 5 indexed citations
18.
Rowe, Suzanne J., Ian White, Santiago Avendaño, & William G. Hill. (2006). Variation between broiler sires in variation within sires.. 1 indexed citations
19.
Rowe, Suzanne J., Ricardo Pong‐Wong, Chris Haley, Sara Knott, & Dirk‐Jan de Koning. (2006). Variance component estimation of additive and dominance QTL effects in outbred populations applied to commercial broilers.. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006. 1 indexed citations
20.
Lovrien, E.W., et al.. (1978). Linkage study of antithrombin III. Cytogenetic and Genome Research. 22(1-6). 319–323. 12 indexed citations

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.

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