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For: Yoshida GM, Yáñez JM. Increased accuracy of genomic predictions for growth under chronic thermal stress in rainbow trout by prioritizing variants from GWAS using imputed sequence data. Evol Appl. [DOI: 10.1111/eva.13240] [Cited by in Crossref: 7] [Cited by in F6Publishing: 10] [Article Influence: 3.5] [Reference Citation Analysis]
Number Citing Articles
1 Vu NT, Phuc TH, Nguyen NH, Van Sang N. Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus. Front Genet 2022;13:1081246. [PMID: 36685869 DOI: 10.3389/fgene.2022.1081246] [Reference Citation Analysis]
2 Chaivichoo P, Sukhavachana S, Khumthong R, Srisapoome P, Chatchaiphan S, Na-nakorn U. Genome–wide association study and genomic prediction of growth traits in bighead catfish (Clarias macrocephalus Günther, 1864). Aquaculture 2023;562:738748. [DOI: 10.1016/j.aquaculture.2022.738748] [Reference Citation Analysis]
3 Sánchez-Roncancio C, García B, Gallardo-Hidalgo J, Yáñez JM. GWAS on Imputed Whole-Genome Sequence Variants Reveal Genes Associated with Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss). Genes (Basel) 2022;14. [PMID: 36672855 DOI: 10.3390/genes14010114] [Reference Citation Analysis]
4 Wang J, Peng W, Chen L, Kangzhu Y, Zhong J. Assessment of Genomic Prediction Strategies after Animal Genome-Wide Association Study.. [DOI: 10.21203/rs.3.rs-2331918/v1] [Reference Citation Analysis]
5 Yáñez JM, Barría A, López ME, Moen T, Garcia BF, Yoshida GM, Xu P. Genome‐wide association and genomic selection in aquaculture. Reviews in Aquaculture 2022. [DOI: 10.1111/raq.12750] [Reference Citation Analysis]
6 Chen G, Zhou Y, Yu X, Wang J, Luo W, Pang M, Tong J. Genome-Wide Association Study Reveals SNPs and Candidate Genes Related to Growth and Body Shape in Bighead Carp (Hypophthalmichthys nobilis). Mar Biotechnol 2022. [DOI: 10.1007/s10126-022-10176-2] [Reference Citation Analysis]
7 Prchal M, D'ambrosio J, Lagarde H, Lallias D, Patrice P, François Y, Poncet C, Desgranges A, Haffray P, Dupont-nivet M, Phocas F. Genome-wide association study and genomic prediction of tolerance to acute hypoxia in rainbow trout. Aquaculture 2022. [DOI: 10.1016/j.aquaculture.2022.739068] [Reference Citation Analysis]
8 Liu D, Xu Z, Zhao W, Wang S, Li T, Zhu K, Liu G, Zhao X, Wang Q, Pan Y, Ma P. Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population. Front Genet 2022;13:940650. [DOI: 10.3389/fgene.2022.940650] [Reference Citation Analysis]
9 Wang Z, Hu H, Sun T, Li X, Lv G, Bai Z, Li J. Genomic selection for improvement of growth traits in triangle sail mussel (Hyriopsis cumingii). Aquaculture 2022. [DOI: 10.1016/j.aquaculture.2022.738692] [Reference Citation Analysis]
10 Song H, Dong T, Yan X, Wang W, Tian Z, Sun A, Dong Y, Zhu H, Hu H. Genomic selection and its research progress in aquaculture breeding. Reviews in Aquaculture. [DOI: 10.1111/raq.12716] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Fraslin C, Yáñez JM, Robledo D, Houston RD. The impact of genetic relationship between training and validation populations on genomic prediction accuracy in Atlantic salmon.. [DOI: 10.1101/2021.09.14.460263] [Reference Citation Analysis]
12 Sandoval-castillo J, Beheregaray LB, Wellenreuther M. Genomic prediction of growth in a commercially, recreationally, and culturally important marine resource, the Australian snapper (Chrysophrys auratus).. [DOI: 10.1101/2021.09.02.458800] [Reference Citation Analysis]