Kyle E. Martin

1.2k total citations
23 papers, 625 citations indexed

About

Kyle E. Martin is a scholar working on Genetics, Nature and Landscape Conservation and Aquatic Science. According to data from OpenAlex, Kyle E. Martin has authored 23 papers receiving a total of 625 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Genetics, 9 papers in Nature and Landscape Conservation and 9 papers in Aquatic Science. Recurrent topics in Kyle E. Martin's work include Genetic and phenotypic traits in livestock (15 papers), Fish Ecology and Management Studies (9 papers) and Aquaculture Nutrition and Growth (8 papers). Kyle E. Martin is often cited by papers focused on Genetic and phenotypic traits in livestock (15 papers), Fish Ecology and Management Studies (9 papers) and Aquaculture Nutrition and Growth (8 papers). Kyle E. Martin collaborates with scholars based in United States, Netherlands and Finland. Kyle E. Martin's co-authors include James E. Parsons, Yniv Palti, Timothy D. Leeds, Guangtu Gao, Roger L. Vallejo, Jason P. Evenhuis, Gregory D. Wiens, Breno Fragomeni, Sixin Liu and Hans Komen and has published in prestigious journals such as Aquaculture, Journal of Animal Science and BMC Genomics.

In The Last Decade

Kyle E. Martin

23 papers receiving 616 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyle E. Martin United States 13 467 282 154 123 63 23 625
Anastasia Bestin France 15 352 0.8× 333 1.2× 136 0.9× 116 0.9× 62 1.0× 25 580
María E. López Chile 15 467 1.0× 248 0.9× 212 1.4× 110 0.9× 103 1.6× 26 667
Supawadee Poompuang Thailand 16 376 0.8× 372 1.3× 163 1.1× 115 0.9× 125 2.0× 45 674
Hsin‐Yuan Tsai Taiwan 8 460 1.0× 229 0.8× 127 0.8× 91 0.7× 64 1.0× 15 656
J. Mota-Velasco United Kingdom 10 234 0.5× 205 0.7× 187 1.2× 77 0.6× 34 0.5× 12 481
Dimitrios Chatziplis Greece 14 347 0.7× 157 0.6× 56 0.4× 59 0.5× 54 0.9× 40 480
Kris A. Christensen Canada 13 281 0.6× 135 0.5× 119 0.8× 116 0.9× 80 1.3× 27 457
Panya Sae‐Lim Norway 12 257 0.6× 308 1.1× 60 0.4× 161 1.3× 68 1.1× 26 517
Liane N. Bassini Chile 10 293 0.6× 189 0.7× 192 1.2× 93 0.8× 66 1.0× 14 435
Cécile Massault Australia 12 251 0.5× 209 0.7× 134 0.9× 41 0.3× 52 0.8× 25 401

Countries citing papers authored by Kyle E. Martin

Since Specialization
Citations

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

Fields of papers citing papers by Kyle E. Martin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyle E. Martin. 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 Kyle E. Martin. The network helps show where Kyle E. Martin may publish in the future.

Co-authorship network of co-authors of Kyle E. Martin

This figure shows the co-authorship network connecting the top 25 collaborators of Kyle E. Martin. A scholar is included among the top collaborators of Kyle E. Martin 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 Kyle E. Martin. Kyle E. Martin 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
2.
Martin, Kyle E., W. M. Snelling, Timothy D. Leeds, et al.. (2024). Accurate genotype imputation from low-coverage whole-genome sequencing data of rainbow trout. G3 Genes Genomes Genetics. 14(9). 4 indexed citations
4.
Liu, Sixin, Kyle E. Martin, Guangtu Gao, et al.. (2022). Identification of Haplotypes Associated With Resistance to Bacterial Cold Water Disease in Rainbow Trout Using Whole-Genome Resequencing. Frontiers in Genetics. 13. 936806–936806. 9 indexed citations
6.
Weber, Gregory M., Kyle E. Martin, Guangtu Gao, et al.. (2021). Comparisons among rainbow trout, Oncorhynchus mykiss, populations of maternal transcript profile associated with egg viability. BMC Genomics. 22(1). 448–448. 4 indexed citations
7.
Liu, Sixin, Guangtu Gao, Ryan M. Layer, et al.. (2021). Identification of High-Confidence Structural Variants in Domesticated Rainbow Trout Using Whole-Genome Sequencing. Frontiers in Genetics. 12. 639355–639355. 12 indexed citations
9.
Evenhuis, Jason P., Roger L. Vallejo, Guangtu Gao, et al.. (2019). Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations. Genetics Selection Evolution. 51(1). 42–42. 32 indexed citations
10.
Ma, Hao, et al.. (2019). Transcriptome analysis of egg viability in rainbow trout, Oncorhynchus mykiss. BMC Genomics. 20(1). 319–319. 15 indexed citations
11.
Liu, Sixin, Roger L. Vallejo, Jason P. Evenhuis, et al.. (2018). Retrospective Evaluation of Marker-Assisted Selection for Resistance to Bacterial Cold Water Disease in Three Generations of a Commercial Rainbow Trout Breeding Population. Frontiers in Genetics. 9. 286–286. 21 indexed citations
12.
Evenhuis, Jason P., Roger L. Vallejo, S. Tsuruta, et al.. (2018). Variance and covariance estimates for resistance to bacterial cold water disease and columnaris disease in two rainbow trout breeding populations1. Journal of Animal Science. 97(3). 1124–1132. 11 indexed citations
13.
Vallejo, Roger L., Sixin Liu, Guangtu Gao, et al.. (2017). Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations. Frontiers in Genetics. 8. 156–156. 57 indexed citations
14.
Vallejo, Roger L., Timothy D. Leeds, Guangtu Gao, et al.. (2017). Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture. Genetics Selection Evolution. 49(1). 17–17. 171 indexed citations
15.
Weber, Gregory M., et al.. (2016). Effects of incubation temperatures on embryonic and larval survival in rainbow trout, Oncorhynchus mykiss. Journal of Applied Aquaculture. 28(4). 285–297. 15 indexed citations
16.
Liu, Sixin, Yniv Palti, Kyle E. Martin, James E. Parsons, & Caird E. Rexroad. (2016). Assessment of genetic differentiation and genetic assignment of commercial rainbow trout strains using a SNP panel. Aquaculture. 468. 120–125. 14 indexed citations
17.
Sae‐Lim, Panya, Antti Kause, H.A. Mulder, et al.. (2013). Genotype-by-environment interaction of growth traits in rainbow trout (Oncorhynchus mykiss): A continental scale study1. Journal of Animal Science. 91(12). 5572–5581. 59 indexed citations
18.
Sae‐Lim, Panya, Hans Komen, Antti Kause, et al.. (2012). Enhancing selective breeding for growth, slaughter traits and overall survival in rainbow trout (Oncorhynchus mykiss). Aquaculture. 372-375. 89–96. 24 indexed citations
19.
Martin, Kyle E., Craig A. Steele, Joseph P. Brunelli, & Gary H. Thorgaard. (2010). Mitochondrial Variation and Biogeographic History of Chinook Salmon. Transactions of the American Fisheries Society. 139(3). 792–802. 11 indexed citations
20.
Brown, Kim H., et al.. (2004). Genetic Analysis of Interior Pacific Northwest Oncorhynchus mykiss Reveals Apparent Ancient Hybridization with Westslope Cutthroat Trout. Transactions of the American Fisheries Society. 133(5). 1078–1088. 16 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026