R. Roehe

8.6k total citations · 4 hit papers
159 papers, 5.6k citations indexed

About

R. Roehe is a scholar working on Genetics, Animal Science and Zoology and Small Animals. According to data from OpenAlex, R. Roehe has authored 159 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Genetics, 82 papers in Animal Science and Zoology and 62 papers in Small Animals. Recurrent topics in R. Roehe's work include Genetic and phenotypic traits in livestock (94 papers), Animal Behavior and Welfare Studies (62 papers) and Animal Nutrition and Physiology (52 papers). R. Roehe is often cited by papers focused on Genetic and phenotypic traits in livestock (94 papers), Animal Behavior and Welfare Studies (62 papers) and Animal Nutrition and Physiology (52 papers). R. Roehe collaborates with scholars based in United Kingdom, Germany and United States. R. Roehe's co-authors include E. Kalm, Mick Watson, Carol-Anne Duthie, Marc Auffret, R.J. Dewhurst, John A. Rooke, Simon P. Turner, N. Prieto, A. Waterhouse and Alan W. Walker and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Nature Biotechnology.

In The Last Decade

R. Roehe

156 papers receiving 5.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A review

2009 385 citations N. Prieto, R. Roehe et al. Meat Science profile →
Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen

2018 352 citations Robert D. Stewart, Marc Auffret et al. Nature Communications profile →
Compendium of 4,941 rumen metagenome-assembled genomes for rumen microbiome biology and enzyme discovery

2019 338 citations Robert D. Stewart, Marc Auffret et al. profile →
Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance

2016 240 citations R. Roehe, R.J. Dewhurst et al. PLoS Genetics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
R. Roehe United Kingdom	39	2.4k	2.0k	1.8k	1.6k	1.2k	159	5.6k
D.W. Pethick Australia	43	4.2k 1.7×	1.3k 0.6×	967 0.5×	968 0.6×	738 0.6×	172	5.7k
Martino Cassandro Italy	43	2.6k 1.1×	3.1k 1.5×	2.6k 1.4×	351 0.2×	862 0.7×	292	5.9k
Giovanni Bittante Italy	46	3.0k 1.2×	4.0k 2.0×	4.5k 2.4×	446 0.3×	803 0.7×	314	7.4k
Nicolas Gengler Belgium	41	2.8k 1.2×	4.4k 2.2×	3.3k 1.8×	752 0.5×	366 0.3×	359	6.4k
R.I. Richardson United Kingdom	40	8.3k 3.4×	1.7k 0.8×	2.0k 1.1×	409 0.3×	1.5k 1.2×	142	10.4k
Mauro Penasa Italy	39	2.0k 0.8×	2.2k 1.1×	2.7k 1.5×	401 0.2×	533 0.4×	213	4.7k
Graham Plastow Canada	47	3.4k 1.4×	4.4k 2.2×	1.6k 0.9×	711 0.4×	1.8k 1.4×	313	8.3k
A. Gilmour Australia	44	1.2k 0.5×	3.0k 1.5×	1.4k 0.8×	412 0.3×	1.0k 0.9×	146	7.5k
G. Simm United Kingdom	37	1.9k 0.8×	3.5k 1.7×	2.5k 1.3×	833 0.5×	239 0.2×	188	4.7k
Nissim Silanikove Israel	46	3.9k 1.6×	2.0k 1.0×	4.4k 2.4×	1.3k 0.8×	754 0.6×	128	8.2k

Countries citing papers authored by R. Roehe

Since Specialization

Citations

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

Fields of papers citing papers by R. Roehe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Roehe. 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 R. Roehe. The network helps show where R. Roehe may publish in the future.

Co-authorship network of co-authors of R. Roehe

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Martínez-Álvaro, Marina, Marc Auffret, Carol-Anne Duthie, et al.. (2024). Temporal stability of the rumen microbiome and its longitudinal associations with performance traits in beef cattle. Scientific Reports. 14(1). 20772–20772. 4 indexed citations

Martínez-Álvaro, Marina, et al.. (2023). KOunt: a reproducible KEGG orthologue abundance workflow. Bioinformatics. 39(8). 2 indexed citations

Díaz, Julia Adriana Calderón, et al.. (2023). 184 Genetic Parameters for Human-Directed Behavior and Intraspecific Social Aggression Traits in Growing Pigs. Journal of Animal Science. 101(Supplement_2). 7–8.

Agha, Saif, et al.. (2022). Genetic Analysis of Novel Behaviour Traits in Pigs Derived from Social Network Analysis. Genes. 13(4). 561–561. 7 indexed citations

Agha, Saif, et al.. (2022). Genetic Associations of Novel Behaviour Traits Derived from Social Network Analysis with Growth, Feed Efficiency, and Carcass Characteristics in Pigs. Genes. 13(9). 1616–1616. 3 indexed citations

Wang, Mengyuan, et al.. (2019). Understanding the relationships between rumen microbiome genes and metabolites to be used for prediction of cattle phenotypes. Ulster University Research Portal (Ulster University). 2 indexed citations

Auffret, Marc, Robert D. Stewart, R.J. Dewhurst, et al.. (2019). Identification of Rumen Microbial Genes Involved in Pathways Linked to Appetite, Growth, and Feed Conversion Efficiency in Cattle. Frontiers in Genetics. 10. 701–701. 48 indexed citations

Stewart, Robert D., Marc Auffret, Timothy J. Snelling, R. Roehe, & Mick Watson. (2018). MAGpy: a reproducible pipeline for the downstream analysis of metagenome-assembled genomes (MAGs). Bioinformatics. 35(12). 2150–2152. 25 indexed citations

Stewart, Robert D., Marc Auffret, Amanda Warr, et al.. (2018). Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen. Nature Communications. 9(1). 870–870. 352 indexed citations breakdown →

10.

Duthie, Carol-Anne, Marie J. Haskell, J. J. Hyslop, et al.. (2017). The impact of divergent breed types and diets on methane emissions, rumen characteristics and performance of finishing beef cattle. animal. 11(10). 1762–1771. 26 indexed citations

11.

Duthie, Carol-Anne, Shane M. Troy, J. J. Hyslop, et al.. (2017). The effect of dietary addition of nitrate or increase in lipid concentrations, alone or in combination, on performance and methane emissions of beef cattle. animal. 12(2). 280–287. 39 indexed citations

12.

Roehe, R., R.J. Dewhurst, Carol-Anne Duthie, et al.. (2016). Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance. PLoS Genetics. 12(2). e1005846–e1005846. 240 indexed citations breakdown →

13.

Turner, Simon P., E.A. Navajas, J. J. Hyslop, et al.. (2011). Associations between response to handling and growth and meat quality in frequently handled Bos taurus beef cattle1. Journal of Animal Science. 89(12). 4239–4248. 65 indexed citations

14.

Prieto, N., E.A. Navajas, R.I. Richardson, et al.. (2010). Predicting beef cuts composition, fatty acids and meat quality characteristics by spiral computed tomography. Meat Science. 86(3). 770–779. 41 indexed citations

15.

Navajas, E.A., R.I. Richardson, C. A. Glasbey, et al.. (2009). Associations betwen beef density by X-ray computed tomography, intramuscular fat and fatty acid composition: preliminary results. Bristol Research (University of Bristol). 2009. 3 indexed citations

16.

Turner, Simon P., R. Roehe, Richard B. D’Eath, et al.. (2009). Genetic validation of postmixing skin injuries in pigs as an indicator of aggressiveness and the relationship with injuries under more stable social conditions. Journal of Animal Science. 87(10). 3076–3082. 99 indexed citations

17.

Roehe, R., Nirman Shrestha, Wagdy Mekkawy, et al.. (2008). Genetic analysis of a two generation selection experiment under outdoor conditions designed to disentangle direct and maternal genetic effects of piglet survival. Proceedings of the British Society of Animal Science. 2008. 105–105. 1 indexed citations

18.

Lambe, N.R., E.A. Navajas, C.P. Schofield, et al.. (2008). The use of various live animal measurements to predict carcass and meat quality in two divergent lamb breeds. Meat Science. 80(4). 1138–1149. 46 indexed citations

19.

Roehe, R.. (2006). Molecular and quantitative genetic determination of protein and lipid deposition during growth of pigs.. 2 indexed citations

20.

Roehe, R., et al.. (2002). Biological growth model as a new selection strategy for improvement of feed efficiency in swine. 18. 84–89. 5 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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