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Journals / Black Sea Journal of Agriculture / 2022 / Cilt: 5 - Sayı: 3

Bibliometric Analysis for Genome-Wide Association Studies in Animal Science

Cem TIRINK
Pages
234–239
Publication Date
2022-10-12
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The bibliometric results show that GWAS within animal science is developing steadily as a field of scientific research and is currently a highly topical issue.

📌 3 Key Takeaways

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Objective & Hypothesis:The main idea of the study is to determine the trends in recent years in the field of animal science, by examining 379 studies with the term "genome-wide association studies" in the title of the article published within the scope of SCI-Expanded between 2007-2021, within the scope of bibliometric analysis.
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Key Findings & Data:In this context, the term of “Genome-Wide Association Studies” was searched in the Web of Science database in the study titles and the bibliometric data of the studies were accessed in Plain text format.
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Conclusion & Impact:The bibliometric results show that GWAS within animal science is developing steadily as a field of scientific research and is currently a highly topical issue.
🔬Design:Research Article
📍Scope:2007-2021 Verileri
⚙️Variables:Domain Parameters

Abstract

The main idea of the study is to determine the trends in recent years in the field of animal science, by examining 379 studies with the term "genome-wide association studies" in the title of the article published within the scope of SCI-Expanded between 2007-2021, within the scope of bibliometric analysis. In this context, the term of “Genome-Wide Association Studies” was searched in the Web of Science database in the study titles and the bibliometric data of the studies were accessed in Plain text format. The bibliometric results show that GWAS within animal science is developing steadily as a field of scientific research and is currently a highly topical issue. GWAS has been one of the most popular research areas due to its application in many different fields such as cell biology, plant sciences, zoology, animal science, etc. In the light of this information, it can be listed as an important contribution that GWAS studies with bibliometric analysis are still up-to-date and that the studies to be done will increase their contribution to animal science.

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Cite This Article

TIRINK, C. (2022). Bibliometric Analysis for Genome-Wide Association Studies in Animal Science. Black Sea Journal of Agriculture, Cilt: 5 - Sayı: 3, 234–239. https://ajindex.com/articles/467240

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References (10)

  1. Abasht B, Lamont SJ. 2007. Genome‐wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population. Anim Genet 38(5): 491-498.
  2. Aria M, Cuccurullo C. 2017. bibliometrix: An R-tool for comprehensive science mapping analysis. J Informetr 11(4): 959-975. Bar-Ilan J. 2008. Informetrics at the beginning of the 21st century-A review. J Informetr 2(1): 1-52. Celik S. 2021. Social network analysis and a model practice. J Orig Stu 2(1): 29-41.
  3. Charlier C, Coppieters W, Rollin F, Desmecht D, Agerholm JS, Cambisano N, Carta E, Dardano S, Dive M, Fasquelle, C, Frennet JC. 2008. Highly effective SNP-based association mapping and management of recessive defects in livestock. Nat Genet 40(4): 449-54.
  4. Ertugrul O, Orman MN, Guneren G. 2002. Some genetic parameters of milk production in the Holstein breed. Turk J Vet Anim Sci 26: 463-469.
  5. Gu X, Feng C, Ma L, Song C, Wang Y, Da Y, Li H, Chen K, Ye S, Ge C, Hu X, Li N. 2011. Genome-wide association study of body weight in chicken F2 resource population. PLoS ONE 6(7): e21872. Han J, Kang HJ, Kim M, Kwon GH. 2020. Mapping the intellectual structure of research on surgery with mixed reality: Bibliometric network analysis (2000–2019). J Biomed Inform 109: 103516. Hayes B, Goddard M. 2010. Genome-wide association and genomic selection in animal breeding. Genome 53(11): 876-883.
  6. Inci H, Celik S, Sogut B, Sengul T, Karakaya E. 2015. Examining the Effects of Different Feather Color on the Characteristics of Interior and Exterior Egg Quality of Japanese Quail by Using Kruskal-Wallis Tests. Turk J Agric Nat Sci 2 (1): 112–118.
  7. Khanzadeh H, Ghavi Hossein-Zadeh N, Ghovvati S. 2020. Genome wide association studies, next generation sequencing and their application in animal breeding and genetics: a review. Iran J Appl Anim Sci 10(3): 395-404.
  8. Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, Henning AK, San Giovanni JP, Mane SM, Mayne ST, Bracken MB, Ferris FL, Ott J, Barnstable C, Hoh J. 2005. Complement factor H polymorphism in age-related macular degeneration. Sci 308(5720): 385-389.
  9. Lipkin E, Mosig MO, Darvasi A, Ezra E, Shalom A, Friedmann A, Soller M. 1988. Quantitative trait locus mapping in dairy cattle by means of selective milk DNA pooling using dinucleotide microsatellite markers: Analysis of milk protein percentage. Genetics 149: 1557-1567.
  10. Long N, Gianola D, Rosa G, Weigel K. 2007. Machine learning classification procedure for selecting SNPs in genomic selectio