These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
2. Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials. Dias KODG; Gezan SA; Guimarães CT; Nazarian A; da Costa E Silva L; Parentoni SN; de Oliveira Guimarães PE; de Oliveira Anoni C; Pádua JMV; de Oliveira Pinto M; Noda RW; Ribeiro CAG; de Magalhães JV; Garcia AAF; de Souza JC; Guimarães LJM; Pastina MM Heredity (Edinb); 2018 Jul; 121(1):24-37. PubMed ID: 29472694 [TBL] [Abstract][Full Text] [Related]
3. Realized genomic selection across generations in a reciprocal recurrent selection breeding program of Simiqueli GF; Resende RT; Takahashi EK; de Sousa JE; Grattapaglia D Front Plant Sci; 2023; 14():1252504. PubMed ID: 37965018 [TBL] [Abstract][Full Text] [Related]
4. Genomic Selection in Rubber Tree Breeding: A Comparison of Models and Methods for Managing G×E Interactions. Souza LM; Francisco FR; Gonçalves PS; Scaloppi Junior EJ; Le Guen V; Fritsche-Neto R; Souza AP Front Plant Sci; 2019; 10():1353. PubMed ID: 31708955 [TBL] [Abstract][Full Text] [Related]
5. Genome optimization via virtual simulation to accelerate maize hybrid breeding. Cheng Q; Jiang S; Xu F; Wang Q; Xiao Y; Zhang R; Zhao J; Yan J; Ma C; Wang X Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34676389 [TBL] [Abstract][Full Text] [Related]
6. Genomic Prediction of Kernel Zinc Concentration in Multiple Maize Populations Using Genotyping-by-Sequencing and Repeat Amplification Sequencing Markers. Guo R; Dhliwayo T; Mageto EK; Palacios-Rojas N; Lee M; Yu D; Ruan Y; Zhang A; San Vicente F; Olsen M; Crossa J; Prasanna BM; Zhang L; Zhang X Front Plant Sci; 2020; 11():534. PubMed ID: 32457778 [TBL] [Abstract][Full Text] [Related]
7. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction. Bandeira E Sousa M; Cuevas J; de Oliveira Couto EG; Pérez-Rodríguez P; Jarquín D; Fritsche-Neto R; Burgueño J; Crossa J G3 (Bethesda); 2017 Jun; 7(6):1995-2014. PubMed ID: 28455415 [TBL] [Abstract][Full Text] [Related]
8. Effects of Different Strategies for Exploiting Genomic Selection in Perennial Ryegrass Breeding Programs. Esfandyari H; Fè D; Tessema BB; Janss LL; Jensen J G3 (Bethesda); 2020 Oct; 10(10):3783-3795. PubMed ID: 32819970 [TBL] [Abstract][Full Text] [Related]
9. Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids. Martins Oliveira IC; Bernardeli A; Soler Guilhen JH; Pastina MM Methods Mol Biol; 2022; 2467():543-567. PubMed ID: 35451790 [TBL] [Abstract][Full Text] [Related]
10. [Genomic selection and its application]. Li HD; Bao ZM; Sun XW Yi Chuan; 2011 Dec; 33(12):1308-16. PubMed ID: 22207376 [TBL] [Abstract][Full Text] [Related]
11. Genomic versus phenotypic selection to improve corn borer resistance and grain yield in maize. Gesteiro N; Ordás B; Butrón A; de la Fuente M; Jiménez-Galindo JC; Samayoa LF; Cao A; Malvar RA Front Plant Sci; 2023; 14():1162440. PubMed ID: 37484478 [TBL] [Abstract][Full Text] [Related]
12. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models. Cuevas J; Crossa J; Montesinos-López OA; Burgueño J; Pérez-Rodríguez P; de Los Campos G G3 (Bethesda); 2017 Jan; 7(1):41-53. PubMed ID: 27793970 [TBL] [Abstract][Full Text] [Related]
13. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives. Crossa J; Pérez-Rodríguez P; Cuevas J; Montesinos-López O; Jarquín D; de Los Campos G; Burgueño J; González-Camacho JM; Pérez-Elizalde S; Beyene Y; Dreisigacker S; Singh R; Zhang X; Gowda M; Roorkiwal M; Rutkoski J; Varshney RK Trends Plant Sci; 2017 Nov; 22(11):961-975. PubMed ID: 28965742 [TBL] [Abstract][Full Text] [Related]
14. Genotyping marker density and prediction models effects in long-term breeding schemes of cross-pollinated crops. DoVale JC; Carvalho HF; Sabadin F; Fritsche-Neto R Theor Appl Genet; 2022 Dec; 135(12):4523-4539. PubMed ID: 36261658 [TBL] [Abstract][Full Text] [Related]
15. Optimizing the allocation of resources for genomic selection in one breeding cycle. Riedelsheimer C; Melchinger AE Theor Appl Genet; 2013 Nov; 126(11):2835-48. PubMed ID: 23982591 [TBL] [Abstract][Full Text] [Related]
16. Improving Genomic Selection With Quantitative Trait Loci and Nonadditive Effects Revealed by Empirical Evidence in Maize. Liu X; Wang H; Hu X; Li K; Liu Z; Wu Y; Huang C Front Plant Sci; 2019; 10():1129. PubMed ID: 31620155 [TBL] [Abstract][Full Text] [Related]
17. Accuracy of genomic selection for a sib-evaluated trait using identity-by-state and identity-by-descent relationships. Vela-Avitúa S; Meuwissen TH; Luan T; Ødegård J Genet Sel Evol; 2015 Feb; 47(1):9. PubMed ID: 25888184 [TBL] [Abstract][Full Text] [Related]
18. Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids. Liang Z; Gupta SK; Yeh CT; Zhang Y; Ngu DW; Kumar R; Patil HT; Mungra KD; Yadav DV; Rathore A; Srivastava RK; Gupta R; Yang J; Varshney RK; Schnable PS; Schnable JC G3 (Bethesda); 2018 Jul; 8(7):2513-2522. PubMed ID: 29794163 [TBL] [Abstract][Full Text] [Related]
19. Genomic selection on shelling percentage and other traits for maize. Sun Q; Wang P; Li W; Li W; Lu S; Yu Y; Zhao M; Meng Z Breed Sci; 2019 Jun; 69(2):266-271. PubMed ID: 31481835 [TBL] [Abstract][Full Text] [Related]