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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

148 related articles for article (PubMed ID: 22101908)

  • 1. Partial least squares regression, support vector machine regression, and transcriptome-based distances for prediction of maize hybrid performance with gene expression data.
    Fu J; Falke KC; Thiemann A; Schrag TA; Melchinger AE; Scholten S; Frisch M
    Theor Appl Genet; 2012 Mar; 124(5):825-33. PubMed ID: 22101908
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Genome properties and prospects of genomic prediction of hybrid performance in a breeding program of maize.
    Technow F; Schrag TA; Schipprack W; Bauer E; Simianer H; Melchinger AE
    Genetics; 2014 Aug; 197(4):1343-55. PubMed ID: 24850820
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Transcriptome-based distance measures for grouping of germplasm and prediction of hybrid performance in maize.
    Frisch M; Thiemann A; Fu J; Schrag TA; Scholten S; Melchinger AE
    Theor Appl Genet; 2010 Jan; 120(2):441-50. PubMed ID: 19911157
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of single-cross hybrid performance in maize using haplotype blocks associated with QTL for grain yield.
    Schrag TA; Maurer HP; Melchinger AE; Piepho HP; Peleman J; Frisch M
    Theor Appl Genet; 2007 May; 114(8):1345-55. PubMed ID: 17323040
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction of hybrid performance in maize with a ridge regression model employed to DNA markers and mRNA transcription profiles.
    Zenke-Philippi C; Thiemann A; Seifert F; Schrag T; Melchinger AE; Scholten S; Frisch M
    BMC Genomics; 2016 Mar; 17():262. PubMed ID: 27025377
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses.
    Schrag TA; Möhring J; Maurer HP; Dhillon BS; Melchinger AE; Piepho HP; Sørensen AP; Frisch M
    Theor Appl Genet; 2009 Feb; 118(4):741-51. PubMed ID: 19048224
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL.
    Schrag TA; Melchinger AE; Sørensen AP; Frisch M
    Theor Appl Genet; 2006 Oct; 113(6):1037-47. PubMed ID: 16896712
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Classification-driven framework to predict maize hybrid field performance from metabolic profiles of young parental roots.
    de Abreu E Lima F; Willmitzer L; Nikoloski Z
    PLoS One; 2018; 13(4):e0196038. PubMed ID: 29698533
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds.
    Schrag TA; Möhring J; Melchinger AE; Kusterer B; Dhillon BS; Piepho HP; Frisch M
    Theor Appl Genet; 2010 Jan; 120(2):451-61. PubMed ID: 19916002
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Small RNA-based prediction of hybrid performance in maize.
    Seifert F; Thiemann A; Schrag TA; Rybka D; Melchinger AE; Frisch M; Scholten S
    BMC Genomics; 2018 May; 19(1):371. PubMed ID: 29783940
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear prediction.
    Maenhout S; De Baets B; Haesaert G
    Theor Appl Genet; 2010 Jan; 120(2):415-27. PubMed ID: 19904522
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Correlation between parental transcriptome and field data for the characterization of heterosis in Zea mays L.
    Thiemann A; Fu J; Schrag TA; Melchinger AE; Frisch M; Scholten S
    Theor Appl Genet; 2010 Jan; 120(2):401-13. PubMed ID: 19888564
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Across-years prediction of hybrid performance in maize using genomics.
    Schrag TA; Schipprack W; Melchinger AE
    Theor Appl Genet; 2019 Apr; 132(4):933-946. PubMed ID: 30498894
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Genomic prediction of hybrid performance in maize with models incorporating dominance and population specific marker effects.
    Technow F; Riedelsheimer C; Schrag TA; Melchinger AE
    Theor Appl Genet; 2012 Oct; 125(6):1181-94. PubMed ID: 22733443
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Performance prediction of F1 hybrids between recombinant inbred lines derived from two elite maize inbred lines.
    Guo T; Li H; Yan J; Tang J; Li J; Zhang Z; Zhang L; Wang J
    Theor Appl Genet; 2013 Jan; 126(1):189-201. PubMed ID: 22972201
    [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. Comparison of maize (Zea mays L.) F1-hybrid and parental inbred line primary root transcriptomes suggests organ-specific patterns of nonadditive gene expression and conserved expression trends.
    Hoecker N; Keller B; Muthreich N; Chollet D; Descombes P; Piepho HP; Hochholdinger F
    Genetics; 2008 Jul; 179(3):1275-83. PubMed ID: 18562640
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Support vector machine regression for the prediction of maize hybrid performance.
    Maenhout S; De Baets B; Haesaert G; Van Bockstaele E
    Theor Appl Genet; 2007 Nov; 115(7):1003-13. PubMed ID: 17849095
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.