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Items: 1 to 20 of 285

1.

Genetic differences based on a beef terminal index are reflected in future phenotypic performance differences in commercial beef cattle.

Connolly SM, Cromie AR, Berry DP.

Animal. 2016 May;10(5):736-45. doi: 10.1017/S1751731115002827. Epub 2016 Jan 6.

PMID:
27075523
2.

Evaluation of developed low-density genotype panels for imputation to higher density in independent dairy and beef cattle populations.

Judge MM, Kearney JF, McClure MC, Sleator RD, Berry DP.

J Anim Sci. 2016 Mar;94(3):949-62. doi: 10.2527/jas.2015-0044.

PMID:
27065257
3.

A genome-wide association study for genetic susceptibility to Mycobacterium bovis infection in dairy cattle identifies a susceptibility QTL on chromosome 23.

Richardson IW, Berry DP, Wiencko HL, Higgins IM, More SJ, McClure J, Lynn DJ, Bradley DG.

Genet Sel Evol. 2016 Mar 9;48(1):19. doi: 10.1186/s12711-016-0197-x.

4.

The potential of Fourier transform infrared spectroscopy of milk samples to predict energy intake and efficiency in dairy cows.

McParland S, Berry DP.

J Dairy Sci. 2016 May;99(5):4056-70. doi: 10.3168/jds.2015-10051.

PMID:
26947296
5.

Effectiveness of mid-infrared spectroscopy to predict the color of bovine milk and the relationship between milk color and traditional milk quality traits.

McDermott A, Visentin G, McParland S, Berry DP, Fenelon MA, De Marchi M.

J Dairy Sci. 2016 May;99(5):3267-73. doi: 10.3168/jds.2015-10424. Epub 2016 Feb 18.

PMID:
26898278
6.

Questionnaire identifying management practices surrounding calving on spring-calving dairy farms and their associations with herd size and herd expansion.

Cummins C, Berry DP, Sayers R, Lorenz I, Kennedy E.

Animal. 2016 May;10(5):868-77. doi: 10.1017/S1751731116000124. Epub 2016 Feb 9.

PMID:
26857400
7.

Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics.

McDermott A, Visentin G, De Marchi M, Berry DP, Fenelon MA, O'Connor PM, Kenny OA, McParland S.

J Dairy Sci. 2016 Apr;99(4):3171-82. doi: 10.3168/jds.2015-9747. Epub 2016 Jan 29.

PMID:
26830742
8.

Genetic relationships between detailed reproductive traits and performance traits in Holstein-Friesian dairy cattle.

Carthy TR, Ryan DP, Fitzgerald AM, Evans RD, Berry DP.

J Dairy Sci. 2016 Feb;99(2):1286-97. doi: 10.3168/jds.2015-9825. Epub 2015 Dec 17.

PMID:
26709166
9.

Differentially Expressed Genes in Endometrium and Corpus Luteum of Holstein Cows Selected for High and Low Fertility Are Enriched for Sequence Variants Associated with Fertility.

Moore SG, Pryce JE, Hayes BJ, Chamberlain AJ, Kemper KE, Berry DP, McCabe M, Cormican P, Lonergan P, Fair T, Butler ST.

Biol Reprod. 2016 Dec;94(1):19. doi: 10.1095/biolreprod.115.132951. Epub 2015 Nov 25.

10.

Inter-relationships among alternative definitions of feed efficiency in grazing lactating dairy cows.

Hurley AM, López-Villalobos N, McParland S, Kennedy E, Lewis E, O'Donovan M, Burke JL, Berry DP.

J Dairy Sci. 2016 Jan;99(1):468-79. doi: 10.3168/jds.2015-9928. Epub 2015 Nov 14.

PMID:
26585474
11.

Stakeholder involvement in establishing a milk quality sub-index in dairy cow breeding goals: a Delphi approach.

Henchion M, McCarthy M, Resconi VC, Berry DP, McParland S.

Animal. 2016 May;10(5):878-91. doi: 10.1017/S1751731115002165. Epub 2015 Nov 17.

PMID:
26573428
12.

Milk Production and Fertility in Cattle.

Berry DP, Friggens NC, Lucy M, Roche JR.

Annu Rev Anim Biosci. 2016 Feb 15;4:269-90. doi: 10.1146/annurev-animal-021815-111406. Epub 2015 Nov 2.

PMID:
26526546
13.

Risk factors associated with lambing traits.

McHugh N, Berry DP, Pabiou T.

Animal. 2016 Jan;10(1):89-95. doi: 10.1017/S1751731115001664. Epub 2015 Aug 12.

PMID:
26264450
14.

Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia.

de Haas Y, Pryce JE, Calus MP, Wall E, Berry DP, Løvendahl P, Krattenmacher N, Miglior F, Weigel K, Spurlock D, Macdonald KA, Hulsegge B, Veerkamp RF.

J Dairy Sci. 2015 Sep;98(9):6522-34. doi: 10.3168/jds.2014-9257. Epub 2015 Jul 15.

PMID:
26188577
15.

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows.

Visentin G, McDermott A, McParland S, Berry DP, Kenny OA, Brodkorb A, Fenelon MA, De Marchi M.

J Dairy Sci. 2015 Sep;98(9):6620-9. doi: 10.3168/jds.2015-9323. Epub 2015 Jul 15.

PMID:
26188572
16.

Detection of selection signatures in dairy and beef cattle using high-density genomic information.

Zhao F, McParland S, Kearney F, Du L, Berry DP.

Genet Sel Evol. 2015 Jun 19;47:49. doi: 10.1186/s12711-015-0127-3.

17.

Machine learning algorithms for the prediction of conception success to a given insemination in lactating dairy cows.

Hempstalk K, McParland S, Berry DP.

J Dairy Sci. 2015 Aug;98(8):5262-73. doi: 10.3168/jds.2014-8984.

PMID:
26074247
18.

Genome-wide association study for calving performance using high-density genotypes in dairy and beef cattle.

Purfield DC, Bradley DG, Evans RD, Kearney FJ, Berry DP.

Genet Sel Evol. 2015 Jun 12;47:47. doi: 10.1186/s12711-015-0126-4.

19.

Curcumin inhibits cancer stem cell phenotypes in ex vivo models of colorectal liver metastases, and is clinically safe and tolerable in combination with FOLFOX chemotherapy.

James MI, Iwuji C, Irving G, Karmokar A, Higgins JA, Griffin-Teal N, Thomas A, Greaves P, Cai H, Patel SR, Morgan B, Dennison A, Metcalfe M, Garcea G, Lloyd DM, Berry DP, Steward WP, Howells LM, Brown K.

Cancer Lett. 2015 Aug 10;364(2):135-41. doi: 10.1016/j.canlet.2015.05.005. Epub 2015 May 12.

20.

Factors associated with the differential in actual gestational age and gestational age predicted from transrectal ultrasonography in pregnant dairy cows.

Fitzgerald AM, Ryan DP, Berry DP.

Theriogenology. 2015 Aug;84(3):358-64. doi: 10.1016/j.theriogenology.2015.03.023. Epub 2015 Mar 28.

PMID:
25933583
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