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.
22. Genomic Studies Reveal Substantial Dominant Effects and Improved Genomic Predictions in an Open-Pollinated Breeding Population of Thavamanikumar S; Arnold RJ; Luo J; Thumma BR G3 (Bethesda); 2020 Oct; 10(10):3751-3763. PubMed ID: 32788286 [TBL] [Abstract][Full Text] [Related]
23. Validation of Genotyping by Sequencing Using Transcriptomics for Diversity and Application of Genomic Selection in Tetraploid Potato. Caruana BM; Pembleton LW; Constable F; Rodoni B; Slater AT; Cogan NOI Front Plant Sci; 2019; 10():670. PubMed ID: 31191581 [TBL] [Abstract][Full Text] [Related]
24. Genome-wide association mapping and genomic prediction for late blight and potato cyst nematode resistance in potato ( Sood S; Bhardwaj V; Bairwa A; Dalamu ; Sharma S; Sharma AK; Kumar A; Lal M; Kumar V Front Plant Sci; 2023; 14():1211472. PubMed ID: 37860256 [TBL] [Abstract][Full Text] [Related]
25. Genomic Prediction of Biomass Yield in Two Selection Cycles of a Tetraploid Alfalfa Breeding Population. Li X; Wei Y; Acharya A; Hansen JL; Crawford JL; Viands DR; Michaud R; Claessens A; Brummer EC Plant Genome; 2015 Jul; 8(2):eplantgenome2014.12.0090. PubMed ID: 33228301 [TBL] [Abstract][Full Text] [Related]
26. Understanding the Effectiveness of Genomic Prediction in Tetraploid Potato. Wilson S; Zheng C; Maliepaard C; Mulder HA; Visser RGF; van der Burgt A; van Eeuwijk F Front Plant Sci; 2021; 12():672417. PubMed ID: 34434201 [TBL] [Abstract][Full Text] [Related]
27. Selective Genotyping and Phenotyping for Optimization of Genomic Prediction Models for Populations with Different Diversity. Ćeran M; Đorđević V; Miladinović J; Vasiljević M; Đukić V; Ranđelović P; Jaćimović S Plants (Basel); 2024 Mar; 13(7):. PubMed ID: 38611503 [TBL] [Abstract][Full Text] [Related]
28. Increasing cassava root yield: Additive-dominant genetic models for selection of parents and clones. de Andrade LRB; Sousa MBE; Wolfe M; Jannink JL; de Resende MDV; Azevedo CF; de Oliveira EJ Front Plant Sci; 2022; 13():1071156. PubMed ID: 36589120 [TBL] [Abstract][Full Text] [Related]
29. Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster ( Vu SV; Gondro C; Nguyen NTH; Gilmour AR; Tearle R; Knibb W; Dove M; Vu IV; Khuong LD; O'Connor W Genes (Basel); 2021 Feb; 12(2):. PubMed ID: 33535381 [TBL] [Abstract][Full Text] [Related]
30. Using drone-retrieved multispectral data for phenomic selection in potato breeding. Maggiorelli A; Baig N; Prigge V; Bruckmüller J; Stich B Theor Appl Genet; 2024 Mar; 137(3):70. PubMed ID: 38446220 [TBL] [Abstract][Full Text] [Related]
31. Use of a Bayesian model including QTL markers increases prediction reliability when test animals are distant from the reference population. Ma P; Lund MS; Aamand GP; Su G J Dairy Sci; 2019 Aug; 102(8):7237-7247. PubMed ID: 31155255 [TBL] [Abstract][Full Text] [Related]
33. Genomic Selection for Wheat Blast in a Diversity Panel, Breeding Panel and Full-Sibs Panel. Juliana P; He X; Marza F; Islam R; Anwar B; Poland J; Shrestha S; Singh GP; Chawade A; Joshi AK; Singh RP; Singh PK Front Plant Sci; 2021; 12():745379. PubMed ID: 35069614 [TBL] [Abstract][Full Text] [Related]
34. Assessment of the genomic prediction accuracy for feed efficiency traits in meat-type chickens. Liu T; Luo C; Wang J; Ma J; Shu D; Lund MS; Su G; Qu H PLoS One; 2017; 12(3):e0173620. PubMed ID: 28278209 [TBL] [Abstract][Full Text] [Related]
35. Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle. van Binsbergen R; Calus MP; Bink MC; van Eeuwijk FA; Schrooten C; Veerkamp RF Genet Sel Evol; 2015 Sep; 47(1):71. PubMed ID: 26381777 [TBL] [Abstract][Full Text] [Related]
36. Graph-based data selection for the construction of genomic prediction models. Maenhout S; De Baets B; Haesaert G Genetics; 2010 Aug; 185(4):1463-75. PubMed ID: 20479144 [TBL] [Abstract][Full Text] [Related]
37. Potential of genotyping-by-sequencing for genomic selection in livestock populations. Gorjanc G; Cleveland MA; Houston RD; Hickey JM Genet Sel Evol; 2015 Mar; 47(1):12. PubMed ID: 25887531 [TBL] [Abstract][Full Text] [Related]
38. 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]
39. Genotype imputation from various low-density SNP panels and its impact on accuracy of genomic breeding values in pigs. Grossi DA; Brito LF; Jafarikia M; Schenkel FS; Feng Z Animal; 2018 Nov; 12(11):2235-2245. PubMed ID: 29706144 [TBL] [Abstract][Full Text] [Related]
40. 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] [Previous] [Next] [New Search]