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 *

188 related articles for article (PubMed ID: 10194684)

  • 1. Genetic and environmental smoothing of lactation curves with cubic splines.
    White IM; Thompson R; Brotherstone S
    J Dairy Sci; 1999 Mar; 82(3):632-8. PubMed ID: 10194684
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Modeling lactation curves and estimation of genetic parameters for first lactation test-day records of French Holstein cows.
    Druet T; Jaffrézic F; Boichard D; Ducrocq V
    J Dairy Sci; 2003 Jul; 86(7):2480-90. PubMed ID: 12906066
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Comparison of random regression test-day models for Polish Black and White cattle.
    Strabel T; Szyda J; Ptak E; Jamrozik J
    J Dairy Sci; 2005 Oct; 88(10):3688-99. PubMed ID: 16162544
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Comparison of random regression models with Legendre polynomials and linear splines for production traits and somatic cell score of Canadian Holstein cows.
    Bohmanova J; Miglior F; Jamrozik J; Misztal I; Sullivan PG
    J Dairy Sci; 2008 Sep; 91(9):3627-38. PubMed ID: 18765621
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Contrasting models for lactation curve analysis.
    Jaffrezic F; White IM; Thompson R; Visscher PM
    J Dairy Sci; 2002 Apr; 85(4):968-75. PubMed ID: 12018443
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model.
    DeGroot BJ; Keown JF; Van Vleck LD; Kachman SD
    Genet Mol Res; 2007 Jun; 6(2):434-44. PubMed ID: 17952867
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modifying the lactation curve to improve lactation milk and persistency.
    Togashi K; Lin CY
    J Dairy Sci; 2003 Apr; 86(4):1487-93. PubMed ID: 12741575
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models.
    Bignardi AB; El Faro L; Cardoso VL; Machado PF; Albuquerque LG
    J Dairy Sci; 2009 Sep; 92(9):4634-40. PubMed ID: 19700726
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Genetic evaluation of Australian dairy cattle for somatic cell scores using multi-trait random regression test-day model.
    Konstantinov KV; Beard KT; Goddard ME; van der Werf JH
    J Anim Breed Genet; 2009 Jun; 126(3):209-15. PubMed ID: 19646149
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An autoregressive repeatability animal model for test-day records in multiple lactations.
    Carvalheira J; Pollak EJ; Quaas RL; Blake RW
    J Dairy Sci; 2002 Aug; 85(8):2040-5. PubMed ID: 12214997
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Genetic evaluation of dairy cattle using test day yields and random regression model.
    Jamrozik J; Schaeffer LR; Dekkers JC
    J Dairy Sci; 1997 Jun; 80(6):1217-26. PubMed ID: 9201594
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Random herd curves in a test-day model for milk, fat, and protein production of dairy cattle in The Netherlands.
    de Roos AP; Harbers AG; de Jong G
    J Dairy Sci; 2004 Aug; 87(8):2693-701. PubMed ID: 15328295
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Relationships between milk yield and somatic cell score in Canadian Holsteins from simultaneous and recursive random regression models.
    Jamrozik J; Bohmanova J; Schaeffer LR
    J Dairy Sci; 2010 Mar; 93(3):1216-33. PubMed ID: 20172242
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Body trait profiles in Holstein-Friesians modeled using random regression.
    Wall E; Coffey MP; Brotherstone S
    J Dairy Sci; 2005 Oct; 88(10):3663-71. PubMed ID: 16162541
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Modeling daily energy balance of dairy cows in the first three lactations.
    Banos G; Coffey MP; Brotherstone S
    J Dairy Sci; 2005 Jun; 88(6):2226-37. PubMed ID: 15905452
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The accuracy of seven mathematical functions in modeling dairy cattle lactation curves based on test-day records from varying sample schemes.
    Silvestre AM; Petim-Batista F; Colaço J
    J Dairy Sci; 2006 May; 89(5):1813-21. PubMed ID: 16606753
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Genetic parameters for test-day electrical conductivity of milk for first-lactation cows from random regression models.
    Norberg E; Rogers GW; Goodling RC; Cooper JB; Madsen P
    J Dairy Sci; 2004 Jun; 87(6):1917-24. PubMed ID: 15453509
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian estimates of covariance components between lactation curve parameters and disease liability in Danish Holstein cows.
    Jakobsen JH; Rekaya R; Jensen J; Sorensen DA; Madsen P; Gianola D; Christensen LG; Pedersen J
    J Dairy Sci; 2003 Sep; 86(9):3000-7. PubMed ID: 14507037
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Detection of different shapes of lactation curve for milk yield in dairy cattle by empirical mathematical models.
    Macciotta NP; Vicario D; Cappio-Borlino A
    J Dairy Sci; 2005 Mar; 88(3):1178-91. PubMed ID: 15738251
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Variance components for test-day milk, fat, and protein yield, and somatic cell score for analyzing management information.
    Caccamo M; Veerkamp RF; de Jong G; Pool MH; Petriglieri R; Licitra G
    J Dairy Sci; 2008 Aug; 91(8):3268-76. PubMed ID: 18650304
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.