BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

860 related articles for article (PubMed ID: 29472694)

  • 1. 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]  

  • 2. Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea.
    Roorkiwal M; Jarquin D; Singh MK; Gaur PM; Bharadwaj C; Rathore A; Howard R; Srinivasan S; Jain A; Garg V; Kale S; Chitikineni A; Tripathi S; Jones E; Robbins KR; Crossa J; Varshney RK
    Sci Rep; 2018 Aug; 8(1):11701. PubMed ID: 30076340
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs.
    Zhang X; Pérez-Rodríguez P; Semagn K; Beyene Y; Babu R; López-Cruz MA; San Vicente F; Olsen M; Buckler E; Jannink JL; Prasanna BM; Crossa J
    Heredity (Edinb); 2015 Mar; 114(3):291-9. PubMed ID: 25407079
    [TBL] [Abstract][Full Text] [Related]  

  • 4. QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance.
    Almeida GD; Makumbi D; Magorokosho C; Nair S; Borém A; Ribaut JM; Bänziger M; Prasanna BM; Crossa J; Babu R
    Theor Appl Genet; 2013 Mar; 126(3):583-600. PubMed ID: 23124431
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Selection of trait-specific markers and multi-environment models improve genomic predictive ability in rice.
    Bhandari A; Bartholomé J; Cao-Hamadoun TV; Kumari N; Frouin J; Kumar A; Ahmadi N
    PLoS One; 2019; 14(5):e0208871. PubMed ID: 31059529
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.
    Acosta-Pech R; Crossa J; de Los Campos G; Teyssèdre S; Claustres B; Pérez-Elizalde S; Pérez-Rodríguez P
    Theor Appl Genet; 2017 Jul; 130(7):1431-1440. PubMed ID: 28401254
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Empirical Comparison of Tropical Maize Hybrids Selected Through Genomic and Phenotypic Selections.
    Beyene Y; Gowda M; Olsen M; Robbins KR; Pérez-Rodríguez P; Alvarado G; Dreher K; Gao SY; Mugo S; Prasanna BM; Crossa J
    Front Plant Sci; 2019; 10():1502. PubMed ID: 31824533
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Numerous genetic loci identified for drought tolerance in the maize nested association mapping populations.
    Li C; Sun B; Li Y; Liu C; Wu X; Zhang D; Shi Y; Song Y; Buckler ES; Zhang Z; Wang T; Li Y
    BMC Genomics; 2016 Nov; 17(1):894. PubMed ID: 27825295
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Selection of Drought Tolerant Maize Hybrids Using Path Coefficient Analysis and Selection Index.
    Dao A; Sanou J; V S Traore E; Gracen V; Danquah EY
    Pak J Biol Sci; 2017; 20(3):132-139. PubMed ID: 29023004
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Increased Predictive Accuracy of Multi-Environment Genomic Prediction Model for Yield and Related Traits in Spring Wheat (
    Tomar V; Singh D; Dhillon GS; Chung YS; Poland J; Singh RP; Joshi AK; Gautam Y; Tiwari BS; Kumar U
    Front Plant Sci; 2021; 12():720123. PubMed ID: 34691100
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. Novel strategies for genomic prediction of untested single-cross maize hybrids using unbalanced historical data.
    Dias KOG; Piepho HP; Guimarães LJM; Guimarães PEO; Parentoni SN; Pinto MO; Noda RW; Magalhães JV; Guimarães CT; Garcia AAF; Pastina MM
    Theor Appl Genet; 2020 Feb; 133(2):443-455. PubMed ID: 31758202
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multi-Trait Genomic Prediction of Yield-Related Traits in US Soft Wheat under Variable Water Regimes.
    Guo J; Khan J; Pradhan S; Shahi D; Khan N; Avci M; Mcbreen J; Harrison S; Brown-Guedira G; Murphy JP; Johnson J; Mergoum M; Esten Mason R; Ibrahim AMH; Sutton R; Griffey C; Babar MA
    Genes (Basel); 2020 Oct; 11(11):. PubMed ID: 33126620
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genomic-enabled Prediction Accuracies Increased by Modeling Genotype × Environment Interaction in Durum Wheat.
    Sukumaran S; Jarquin D; Crossa J; Reynolds M
    Plant Genome; 2018 Jul; 11(2):. PubMed ID: 30025014
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Genome-based trait prediction in multi- environment breeding trials in groundnut.
    Pandey MK; Chaudhari S; Jarquin D; Janila P; Crossa J; Patil SC; Sundravadana S; Khare D; Bhat RS; Radhakrishnan T; Hickey JM; Varshney RK
    Theor Appl Genet; 2020 Nov; 133(11):3101-3117. PubMed ID: 32809035
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multi-trait Genomic Prediction Model Increased the Predictive Ability for Agronomic and Malting Quality Traits in Barley (
    Bhatta M; Gutierrez L; Cammarota L; Cardozo F; Germán S; Gómez-Guerrero B; Pardo MF; Lanaro V; Sayas M; Castro AJ
    G3 (Bethesda); 2020 Mar; 10(3):1113-1124. PubMed ID: 31974097
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Genomic prediction applied to multiple traits and environments in second season maize hybrids.
    de Oliveira AA; Resende MFR; Ferrão LFV; Amadeu RR; Guimarães LJM; Guimarães CT; Pastina MM; Margarido GRA
    Heredity (Edinb); 2020 Aug; 125(1-2):60-72. PubMed ID: 32472060
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.).
    Trachsel S; Dhliwayo T; Gonzalez Perez L; Mendoza Lugo JA; Trachsel M
    PLoS One; 2019; 14(3):e0212200. PubMed ID: 30893307
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Yield gains and associated changes in an early yellow bi-parental maize population following genomic selection for Striga resistance and drought tolerance.
    Badu-Apraku B; Talabi AO; Fakorede MAB; Fasanmade Y; Gedil M; Magorokosho C; Asiedu R
    BMC Plant Biol; 2019 Apr; 19(1):129. PubMed ID: 30953477
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 43.