Rohan L. Fernando

14.9k total citations · 3 hit papers
211 papers, 10.7k citations indexed

About

Rohan L. Fernando is a scholar working on Genetics, Plant Science and Animal Science and Zoology. According to data from OpenAlex, Rohan L. Fernando has authored 211 papers receiving a total of 10.7k indexed citations (citations by other indexed papers that have themselves been cited), including 181 papers in Genetics, 101 papers in Plant Science and 40 papers in Animal Science and Zoology. Recurrent topics in Rohan L. Fernando's work include Genetic and phenotypic traits in livestock (169 papers), Genetic Mapping and Diversity in Plants and Animals (138 papers) and Genetics and Plant Breeding (95 papers). Rohan L. Fernando is often cited by papers focused on Genetic and phenotypic traits in livestock (169 papers), Genetic Mapping and Diversity in Plants and Animals (138 papers) and Genetics and Plant Breeding (95 papers). Rohan L. Fernando collaborates with scholars based in United States, New Zealand and Türkiye. Rohan L. Fernando's co-authors include Dorian J. Garrick, Jack C. M. Dekkers, David Habier, Daniel Gianola, Kadir Kızılkaya, Michael Grossman, Jeremy F. Taylor, Hao Cheng, Alessandra Stella and Jean‐Luc Jannink and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Rohan L. Fernando

209 papers receiving 10.4k 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.

The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values

2007 977 citations David Habier, Rohan L. Fernando et al. Genetics profile →
Extension of the bayesian alphabet for genomic selection

2011 887 citations David Habier, Rohan L. Fernando et al. profile →
Deregressing estimated breeding values and weighting information for genomic regression analyses

2009 502 citations Dorian J. Garrick, Jeremy F. Taylor et al. Genetics Selection Evolution profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rohan L. Fernando United States	50	9.3k	5.3k	1.6k	1.2k	702	211	10.7k
Andrés Legarra France	47	8.8k 0.9×	4.1k 0.8×	1.6k 1.0×	1.6k 1.3×	344 0.5×	175	9.4k
Dorian J. Garrick New Zealand	50	7.9k 0.9×	3.0k 0.6×	2.2k 1.3×	2.1k 1.7×	914 1.3×	318	10.2k
P.M. VanRaden United States	56	13.0k 1.4×	5.6k 1.1×	1.9k 1.2×	4.0k 3.2×	835 1.2×	223	14.2k
John Woolliams United Kingdom	51	7.9k 0.9×	2.6k 0.5×	1.6k 1.0×	2.5k 2.0×	824 1.2×	366	10.3k
M.P.L. Calus Netherlands	43	6.2k 0.7×	3.1k 0.6×	1.1k 0.7×	1.5k 1.2×	382 0.5×	239	7.1k
Guilherme J. M. Rosa United States	51	5.6k 0.6×	2.2k 0.4×	1.7k 1.1×	2.4k 1.9×	1.2k 1.7×	337	8.8k
J. H. J. van der Werf Australia	46	6.1k 0.7×	1.8k 0.3×	1.9k 1.2×	1.9k 1.5×	478 0.7×	347	7.2k
Henner Simianer Germany	43	4.9k 0.5×	1.5k 0.3×	1.3k 0.8×	1.1k 0.9×	544 0.8×	212	6.1k
Daniel Gianola United States	66	13.8k 1.5×	7.1k 1.3×	2.5k 1.6×	3.7k 3.0×	1.1k 1.5×	353	16.6k
T.H.E. Meuwissen Norway	52	14.0k 1.5×	6.8k 1.3×	2.1k 1.3×	2.1k 1.7×	1.4k 2.0×	270	16.2k

Countries citing papers authored by Rohan L. Fernando

Since Specialization

Citations

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

Fields of papers citing papers by Rohan L. Fernando

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rohan L. Fernando. 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 Rohan L. Fernando. The network helps show where Rohan L. Fernando may publish in the future.

Co-authorship network of co-authors of Rohan L. Fernando

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

All Works

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20 of 20 papers shown

Melchinger, Albrecht E., et al.. (2024). Optimizing selection based on BLUPs or BLUEs in multiple sets of genotypes differing in their population parameters. Theoretical and Applied Genetics. 137(5). 104–104. 1 indexed citations

Melchinger, Albrecht E., Rohan L. Fernando, Christian Stricker, Chris‐Carolin Schön, & Hans-Jürgen Auinger. (2023). Genomic prediction in hybrid breeding: I. Optimizing the training set design. Theoretical and Applied Genetics. 136(8). 176–176. 7 indexed citations

Garrick, Dorian J., et al.. (2022). XSim version 2: simulation of modern breeding programs. G3 Genes Genomes Genetics. 12(4). 9 indexed citations

Cheng, Jian, Rohan L. Fernando, Hao Cheng, et al.. (2021). Genome-wide association study of disease resilience traits from a natural polymicrobial disease challenge model in pigs identifies the importance of the major histocompatibility complex region. G3 Genes Genomes Genetics. 12(3). 12 indexed citations

Gianola, Daniel, Rohan L. Fernando, & Dorian J. Garrick. (2019). A certain invariance property of BLUE in a whole‐genome regression context. Journal of Animal Breeding and Genetics. 136(2). 113–117. 1 indexed citations

Thaller, Georg, et al.. (2019). Efficient genetic value prediction using incomplete omics data. Theoretical and Applied Genetics. 132(4). 1211–1222. 9 indexed citations

Cheng, Hao, Rohan L. Fernando, & Dorian J. Garrick. (2018). JWAS: Julia implementation of Whole-genome Analyses Software. Proceedings of the World Congress on Genetics Applied to Livestock Production. 859. 6 indexed citations

Cheng, Hao, Kadir Kızılkaya, Jian Zeng, Dorian J. Garrick, & Rohan L. Fernando. (2018). Genomic Prediction from Multiple-Trait Bayesian Regression Methods Using Mixture Priors. Genetics. 209(1). 89–103. 49 indexed citations

Hsu, Wan‐Ling, Dorian J. Garrick, & Rohan L. Fernando. (2017). The Accuracy and Bias of Single-Step Genomic Prediction for Populations Under Selection. G3 Genes Genomes Genetics. 7(8). 2685–2694. 28 indexed citations

10.

Wolc, Anna, Rohan L. Fernando, Jack C. M. Dekkers, et al.. (2014). Prediction Accuracy of Pedigree and Genomic Estimated Breeding Values over Generations in Layer Chickens. Iowa State University Digital Repository (Iowa State University). 326. 1 indexed citations

11.

Saatchi, Mahdi, Stephanie McKay, Megan M Rolf, et al.. (2011). Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation. Genetics Selection Evolution. 43(1). 40–40. 165 indexed citations

12.

Habier, David, Rohan L. Fernando, & Dorian J. Garrick. (2010). A combined strategy to infer high-density SNP haplotypes in large pedigrees.. Proceedings of the World Congress on Genetics Applied to Livestock Production. 915. 4 indexed citations

13.

Koltes, James E., Bishnu Prasad Mishra, Dinesh Kumar, et al.. (2009). A nonsense mutation in cGMP-dependent type II protein kinase ( PRKG2 ) causes dwarfism in American Angus cattle. Proceedings of the National Academy of Sciences. 106(46). 19250–19255. 39 indexed citations

14.

Fernando, Rohan L., et al.. (2007). Genomic selection for marker-assisted improvement in line crosses. Theoretical and Applied Genetics. 115(5). 665–674. 37 indexed citations

15.

Zhao, Honghua, Jack C. M. Dekkers, & Rohan L. Fernando. (2006). Power and precision of regression-based linkage disequilibrium mapping of QTL.. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006. 4 indexed citations

16.

Fernando, Rohan L., et al.. (2006). Genomic selection for composite line development using low density marker maps.. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006. 22–65. 4 indexed citations

17.

Totir, Liviu R., Rohan L. Fernando, Jack C. M. Dekkers, Soledad Fernández, & Bernt Guldbrandtsen. (2004). The effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP. Genetics Selection Evolution. 36(1). 29–48. 6 indexed citations

18.

Fernando, Rohan L., et al.. (1998). Genetic Evaluation by Best Linear Unbiased Prediction Using Marker and Trait Information in a Multibreed Population. Genetics. 148(1). 507–515. 16 indexed citations

19.

Misztal, I., Rohan L. Fernando, Michael Grossman, T.J. Lawlor, & M. Łukaszewicz. (1995). Dominance and epistatic effects in genetic evaluation of farm animals. Animal Science Papers and Reports. 13(4). 251–266. 7 indexed citations

20.

Eijk, Michiel J. T. van, et al.. (1992). Development of persistent lymphocytosis in cattle is closely associated with DRB2. Immunogenetics. 37(1). 64–68. 23 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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