Michael K. Dyck

2.3k total citations
90 papers, 1.6k citations indexed

About

Michael K. Dyck is a scholar working on Genetics, Public Health, Environmental and Occupational Health and Molecular Biology. According to data from OpenAlex, Michael K. Dyck has authored 90 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Genetics, 24 papers in Public Health, Environmental and Occupational Health and 23 papers in Molecular Biology. Recurrent topics in Michael K. Dyck's work include Reproductive Biology and Fertility (23 papers), Genetic and phenotypic traits in livestock (19 papers) and Animal Behavior and Welfare Studies (18 papers). Michael K. Dyck is often cited by papers focused on Reproductive Biology and Fertility (23 papers), Genetic and phenotypic traits in livestock (19 papers) and Animal Behavior and Welfare Studies (18 papers). Michael K. Dyck collaborates with scholars based in Canada, United States and Netherlands. Michael K. Dyck's co-authors include Walter T. Dixon, G. R. Foxcroft, Susan Novak, John C. S. Harding, Francois Paradis, Marc‐André Sirard, A. Ruiz-Sanchez, F. Pothier, Graham Plastow and Dan Lacroix and has published in prestigious journals such as Nature Biotechnology, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Michael K. Dyck

83 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael K. Dyck Canada 22 588 468 416 414 405 90 1.6k
W. L. Flowers United States 23 366 0.6× 321 0.7× 428 1.0× 359 0.9× 300 0.7× 53 1.5k
Mongkol Techakumphu Thailand 23 576 1.0× 1.1k 2.3× 319 0.8× 515 1.2× 878 2.2× 154 2.1k
T. Wise United States 25 932 1.6× 504 1.1× 252 0.6× 560 1.4× 517 1.3× 84 1.9k
T. K. Mohanty India 25 672 1.1× 621 1.3× 368 0.9× 869 2.1× 869 2.1× 227 2.0k
J. W. Knight United States 21 606 1.0× 293 0.6× 286 0.7× 484 1.2× 180 0.4× 72 1.7k
Márcio Nunes Corrêa Brazil 18 395 0.7× 233 0.5× 284 0.7× 696 1.7× 171 0.4× 180 1.3k
Miki Sakatani Japan 21 382 0.6× 639 1.4× 406 1.0× 469 1.1× 346 0.9× 53 1.4k
W. F. Pope United States 25 652 1.1× 685 1.5× 211 0.5× 872 2.1× 346 0.9× 64 1.7k
J. Rátky Hungary 19 315 0.5× 579 1.2× 145 0.3× 344 0.8× 419 1.0× 67 1.1k
Koji Yoshioka Japan 25 673 1.1× 1.3k 2.9× 231 0.6× 402 1.0× 698 1.7× 79 2.2k

Countries citing papers authored by Michael K. Dyck

Since Specialization
Citations

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

Fields of papers citing papers by Michael K. Dyck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael K. Dyck. 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 Michael K. Dyck. The network helps show where Michael K. Dyck may publish in the future.

Co-authorship network of co-authors of Michael K. Dyck

This figure shows the co-authorship network connecting the top 25 collaborators of Michael K. Dyck. A scholar is included among the top collaborators of Michael K. Dyck 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 Michael K. Dyck. Michael K. Dyck 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.
Lonergan, Steven M., Kyu‐Sang Lim, Jian Cheng, et al.. (2023). Plasma protein levels of young healthy pigs as indicators of disease resilience. Journal of Animal Science. 101. 5 indexed citations
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Wang, Kun, Rabban Mangat, Bimol C. Roy, et al.. (2021). Exploring Increased Intestinal Lipid Absorption and Identifying Strategies to Improve Pork Quality in Low-Birth-Weight Swine. Current Developments in Nutrition. 5. 547–547. 1 indexed citations
6.
Cheng, Jian, Austin M. Putz, Qian Dong, et al.. (2021). Effect of a genetic marker for the GBP5 gene on resilience to a polymicrobial natural disease challenge in pigs. Livestock Science. 244. 104399–104399. 9 indexed citations
7.
Bortolozzo, Fernando Pandolfo, Stephen Tsoi, Michael K. Dyck, et al.. (2020). Postnatal development of skeletal muscle in pigs with intrauterine growth restriction: morphofunctional phenotype and molecular mechanisms. Journal of Anatomy. 236(5). 840–853. 29 indexed citations
8.
Putz, Austin M., Zhiquan Wang, Frédéric Fortin, et al.. (2020). Exploring Phenotypes for Disease Resilience in Pigs Using Complete Blood Count Data From a Natural Disease Challenge Model. Frontiers in Genetics. 11. 216–216. 21 indexed citations
9.
Foxcroft, G. R., et al.. (2020). Prenatal programming of postnatal development in the pig. Bioscientifica Proceedings. 2 indexed citations
10.
Fouhse, Janelle M., Stephen Tsoi, Jennifer Patterson, et al.. (2019). Outcomes of a low birth weight phenotype on piglet gut microbial composition and intestinal transcriptomic profile. Canadian Journal of Animal Science. 100(1). 47–58. 3 indexed citations
11.
Zhang, Chunyan, Jennifer Patterson, Stephen Tsoi, et al.. (2018). GWAS in production nucleus sows using a 650K SNP Chip to explore component traits underlying a repeatable low litter birth weight phenotype. Proceedings of the World Congress on Genetics Applied to Livestock Production. 567. 3 indexed citations
12.
Pasternak, J. Alex, et al.. (2017). Intrauterine delivery of subunit vaccines induces a systemic and mucosal immune response in rabbits. American Journal of Reproductive Immunology. 78(5). 12 indexed citations
13.
Tsoi, Stephen, et al.. (2016). Accurate and Phenol Free DNA Sexing of Day 30 Porcine Embryos by PCR. Journal of Visualized Experiments. 53301–53301. 8 indexed citations
14.
Zhou, Chi, J.R. Dobrinsky, Stephen Tsoi, et al.. (2014). Characterization of the Altered Gene Expression Profile in Early Porcine Embryos Generated from Parthenogenesis and Somatic Cell Chromatin Transfer. PLoS ONE. 9(3). e91728–e91728. 9 indexed citations
15.
Dyck, Michael K., Chi Zhou, Stephen Tsoi, et al.. (2014). Reproductive technologies and the porcine embryonic transcriptome. Animal Reproduction Science. 149(1-2). 11–18. 14 indexed citations
16.
Novak, Susan, Francois Paradis, Jennifer Patterson, et al.. (2011). Temporal candidate gene expression in the sow placenta and embryo during early gestation and effect of maternal Progenos supplementation on embryonic and placental development. Reproduction Fertility and Development. 24(4). 550–558. 9 indexed citations
17.
Novak, Susan, Trevor A. Smith, Francois Paradis, et al.. (2010). Biomarkers of in vivo fertility in sperm and seminal plasma of fertile stallions. Theriogenology. 74(6). 956–967. 106 indexed citations
18.
Novak, Susan, Francois Paradis, Gordon K. Murdoch, et al.. (2009). Temporal candidate gene expression patterns in the sow placenta during early gestation and the effect of maternal L-arginine supplementation.. PubMed. 66. 201–2. 5 indexed citations
19.
Vinsky, Michael, Francois Paradis, Walter T. Dixon, Michael K. Dyck, & G. R. Foxcroft. (2007). Ontogeny of metabolic effects on embryonic development in lactating and weaned primiparous sows. Reproduction Fertility and Development. 19(5). 603–611. 4 indexed citations
20.
Dyck, Michael K., et al.. (1999). Seminal vesicle production and secretion of growth hormone into seminal fluid. Nature Biotechnology. 17(11). 1087–1090. 22 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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