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Items: 1 to 50 of 160

1.

Technical Note: An R package for Fitting Sparse Neural Networks with Application in Animal Breeding.

Wang Y, Mi X, Rosa GJM, Chen Z, Lin P, Wang S, Bao Z.

J Anim Sci. 2018 Feb 24. doi: 10.1093/jas/sky071. [Epub ahead of print]

PMID:
29529218
2.

Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.

Lopes FB, Wu XL, Li H, Xu J, Perkins T, Genho J, Ferretti R, Tait RG Jr, Bauck S, Rosa GJM.

J Anim Breed Genet. 2018 Feb;135(1):14-27. doi: 10.1111/jbg.12312.

PMID:
29345073
3.

Applying family analyses to electronic health records to facilitate genetic research.

Huang X, Elston RC, Rosa GJ, Mayer J, Ye Z, Kitchner T, Brilliant MH, Page D, Hebbring SJ, Stegle O.

Bioinformatics. 2018 Feb 15;34(4):635-642. doi: 10.1093/bioinformatics/btx569.

PMID:
28968884
4.

Genome-wide association and pathway-based analysis using latent variables related to milk protein composition and cheesemaking traits in dairy cattle.

Dadousis C, Pegolo S, Rosa GJM, Bittante G, Cecchinato A.

J Dairy Sci. 2017 Nov;100(11):9085-9102. doi: 10.3168/jds.2017-13219. Epub 2017 Aug 24.

PMID:
28843680
5.

Causal effect of prolificacy on milk yield in dairy sheep using propensity score.

Ferreira VC, Thomas DL, Valente BD, Rosa GJM.

J Dairy Sci. 2017 Oct;100(10):8443-8450. doi: 10.3168/jds.2017-12907. Epub 2017 Aug 2.

PMID:
28780093
6.

Genomewide association mapping and pathway analysis of meat tenderness in Polled Nellore cattle.

Castro LM, Rosa GJM, Lopes FB, Regitano LCA, Rosa AJM, Magnabosco CU.

J Anim Sci. 2017 May;95(5):1945-1956. doi: 10.2527/jas.2016.1348.

PMID:
28727016
7.

Bayesian analyses of genetic parameters for growth traits in Nellore cattle raised on pasture.

Lopes FB, Ferreira JL, Lobo RB, Rosa GJM.

Genet Mol Res. 2017 Jul 6;16(3). doi: 10.4238/gmr16039606.

PMID:
28692120
8.

Bayesian Networks Illustrate Genomic and Residual Trait Connections in Maize (Zea mays L.).

Töpner K, Rosa GJM, Gianola D, Schön CC.

G3 (Bethesda). 2017 Aug 7;7(8):2779-2789. doi: 10.1534/g3.117.044263.

9.

Evaluation of longevity modeling censored records in Nellore.

Garcia DA, Rosa GJM, Valente BD, Carvalheiro R, Fernandes Júnior GA, Albuquerque LG.

Animal. 2017 Dec;11(12):2113-2119. doi: 10.1017/S1751731117001136. Epub 2017 May 23.

PMID:
28534726
10.

Special Issue: Quantitative and statistical genetics-papers in honour of Daniel Gianola.

Simianer H, Rosa GJM, Mäki-Tanila A.

J Anim Breed Genet. 2017 Jun;134(3):173-174. doi: 10.1111/jbg.12279. No abstract available.

PMID:
28508484
11.

Predictive equations for maximal respiratory pressures of children aged 7-10.

da Rosa GJ, Morcillo AM, de Assumpção MS, Schivinski CIS.

Braz J Phys Ther. 2017 Jan - Feb;21(1):30-36. doi: 10.1016/j.bjpt.2016.04.002. Epub 2017 Jan 14.

12.

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

Somavilla AL, Regitano LCA, Rosa GJM, Mokry FB, Mudadu MA, Tizioto PC, Oliveira PSN, Souza MM, Coutinho LL, Munari DP.

G3 (Bethesda). 2017 Jun 7;7(6):1855-1859. doi: 10.1534/g3.117.041442.

13.

Genome-wide association analysis in dogs implicates 99 loci as risk variants for anterior cruciate ligament rupture.

Baker LA, Kirkpatrick B, Rosa GJ, Gianola D, Valente B, Sumner JP, Baltzer W, Hao Z, Binversie EE, Volstad N, Piazza A, Sample SJ, Muir P.

PLoS One. 2017 Apr 5;12(4):e0173810. doi: 10.1371/journal.pone.0173810. eCollection 2017.

14.

A predictive assessment of genetic correlations between traits in chickens using markers.

Momen M, Mehrgardi AA, Sheikhy A, Esmailizadeh A, Fozi MA, Kranis A, Valente BD, Rosa GJ, Gianola D.

Genet Sel Evol. 2017 Feb 1;49(1):16. doi: 10.1186/s12711-017-0290-9.

15.

Pathway-based genome-wide association analysis of milk coagulation properties, curd firmness, cheese yield, and curd nutrient recovery in dairy cattle.

Dadousis C, Pegolo S, Rosa GJM, Gianola D, Bittante G, Cecchinato A.

J Dairy Sci. 2017 Feb;100(2):1223-1231. doi: 10.3168/jds.2016-11587. Epub 2016 Dec 14.

PMID:
27988128
16.

Genome scan for postmortem carcass traits in Nellore cattle.

Júnior GA, Costa RB, de Camargo GM, Carvalheiro R, Rosa GJ, Baldi F, Garcia DA, Gordo DG, Espigolan R, Takada L, Magalhães AF, Bresolin T, Feitosa FL, Chardulo LA, de Oliveira HN, de Albuquerque LG.

J Anim Sci. 2016 Oct;94(10):4087-4095. doi: 10.2527/jas.2016-0632.

PMID:
27898882
17.

Inferring phenotypic causal structures among meat quality traits and the application of a structural equation model in Japanese Black cattle.

Inoue K, Valente BD, Shoji N, Honda T, Oyama K, Rosa GJ.

J Anim Sci. 2016 Oct;94(10):4133-4142. doi: 10.2527/jas.2016-0554.

PMID:
27898842
18.

Genome-wide association study for cheese yield and curd nutrient recovery in dairy cows.

Dadousis C, Biffani S, Cipolat-Gotet C, Nicolazzi EL, Rosa GJM, Gianola D, Rossoni A, Santus E, Bittante G, Cecchinato A.

J Dairy Sci. 2017 Feb;100(2):1259-1271. doi: 10.3168/jds.2016-11586. Epub 2016 Nov 23.

PMID:
27889122
19.

Accuracy of genomic breeding values for meat tenderness in Polled Nellore cattle.

Magnabosco CU, Lopes FB, Fragoso RC, Eifert EC, Valente BD, Rosa GJ, Sainz RD.

J Anim Sci. 2016 Jul;94(7):2752-60. doi: 10.2527/jas.2016-0279.

PMID:
27482662
20.

Comparison of models for the genetic evaluation of reproductive traits with censored data in Nellore cattle.

Garcia DA, Rosa GJ, Valente BD, Carvalheiro R, Albuquerque LG.

J Anim Sci. 2016 Jun;94(6):2297-306. doi: 10.2527/jas.2016-0273.

PMID:
27285907
21.

Estimation of genetic parameters for longevity considering the cow's age at last calving.

Caetano SL, Rosa GJ, Savegnago RP, Ramos SB, Bernardes PA, Bezerra LA, Lôbo RB, de Paz CC, Munari DP.

J Appl Genet. 2017 Feb;58(1):103-109. doi: 10.1007/s13353-016-0353-6. Epub 2016 Jun 4.

PMID:
27262297
22.

Incorporating parent-of-origin effects in whole-genome prediction of complex traits.

Hu Y, Rosa GJ, Gianola D.

Genet Sel Evol. 2016 Apr 18;48:34. doi: 10.1186/s12711-016-0213-1.

23.

Genome-wide association mapping and pathway analysis of leukosis incidence in a US Holstein cattle population.

Abdalla EA, Peñagaricano F, Byrem TM, Weigel KA, Rosa GJ.

Anim Genet. 2016 Aug;47(4):395-407. doi: 10.1111/age.12438. Epub 2016 Apr 19.

PMID:
27090879
24.

Relationship between calving difficulty and fertility traits in first-parity Iranian Holsteins under standard and recursive models.

Mokhtari MS, Moradi Shahrbabak M, Nejati Javaremi A, Rosa GJ.

J Anim Breed Genet. 2016 Dec;133(6):513-522. doi: 10.1111/jbg.12212. Epub 2016 Apr 17.

PMID:
27086976
25.

Bayesian Variable Selection in Multilevel Item Response Theory Models with Application in Genomics.

Fragoso TM, de Andrade M, Pereira AC, Rosa GJ, Soler JM.

Genet Epidemiol. 2016 Apr;40(3):253-63. doi: 10.1002/gepi.21960.

PMID:
27027518
26.

Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

Abdollahi-Arpanahi R, Morota G, Valente BD, Kranis A, Rosa GJ, Gianola D.

Genet Sel Evol. 2016 Feb 3;48:10. doi: 10.1186/s12711-016-0187-z.

27.

Genomic prediction of breeding values for carcass traits in Nellore cattle.

Fernandes Júnior GA, Rosa GJ, Valente BD, Carvalheiro R, Baldi F, Garcia DA, Gordo DG, Espigolan R, Takada L, Tonussi RL, de Andrade WB, Magalhães AF, Chardulo LA, Tonhati H, de Albuquerque LG.

Genet Sel Evol. 2016 Jan 29;48:7. doi: 10.1186/s12711-016-0188-y.

28.

Short communication: Genetic correlation of bovine leukosis incidence with somatic cell score and milk yield in a US Holstein population.

Abdalla EA, Weigel KA, Byrem TM, Rosa GJM.

J Dairy Sci. 2016 Mar;99(3):2005-2009. doi: 10.3168/jds.2015-9833. Epub 2016 Jan 6.

PMID:
26778307
29.

Searching for causal networks involving latent variables in complex traits: Application to growth, carcass, and meat quality traits in pigs.

Peñagaricano F, Valente BD, Steibel JP, Bates RO, Ernst CW, Khatib H, Rosa GJ.

J Anim Sci. 2015 Oct;93(10):4617-23. doi: 10.2527/jas.2015-9213.

PMID:
26523553
30.

Exploring causal networks underlying fat deposition and muscularity in pigs through the integration of phenotypic, genotypic and transcriptomic data.

Peñagaricano F, Valente BD, Steibel JP, Bates RO, Ernst CW, Khatib H, Rosa GJ.

BMC Syst Biol. 2015 Sep 16;9:58. doi: 10.1186/s12918-015-0207-6.

31.

Prediction of Plant Height in Arabidopsis thaliana Using DNA Methylation Data.

Hu Y, Morota G, Rosa GJ, Gianola D.

Genetics. 2015 Oct;201(2):779-93. doi: 10.1534/genetics.115.177204. Epub 2015 Aug 6.

32.

A GWAS assessment of the contribution of genomic imprinting to the variation of body mass index in mice.

Hu Y, Rosa GJ, Gianola D.

BMC Genomics. 2015 Aug 5;16:576. doi: 10.1186/s12864-015-1721-z.

33.

Bootstrap study of genome-enabled prediction reliabilities using haplotype blocks across Nordic Red cattle breeds.

Cuyabano BC, Su G, Rosa GJ, Lund MS, Gianola D.

J Dairy Sci. 2015 Oct;98(10):7351-63. doi: 10.3168/jds.2015-9360. Epub 2015 Jul 29.

34.

Survival in crossbred lambs: Breed and heterosis effects.

Ferreira VC, Rosa GJ, Berger YM, Thomas DL.

J Anim Sci. 2015 Mar;93(3):912-9. doi: 10.2527/jas.2014-8556.

PMID:
26020869
35.

Defining window-boundaries for genomic analyses using smoothing spline techniques.

Beissinger TM, Rosa GJ, Kaeppler SM, Gianola D, de Leon N.

Genet Sel Evol. 2015 Apr 17;47:30. doi: 10.1186/s12711-015-0105-9.

36.

The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models.

Valente BD, Morota G, Peñagaricano F, Gianola D, Weigel K, Rosa GJ.

Genetics. 2015 Jun;200(2):483-94. doi: 10.1534/genetics.114.169490. Epub 2015 Apr 23.

37.

Assessment of bagging GBLUP for whole-genome prediction of broiler chicken traits.

Abdollahi-Arpanahi R, Morota G, Valente BD, Kranis A, Rosa GJ, Gianola D.

J Anim Breed Genet. 2015 Jun;132(3):218-28. doi: 10.1111/jbg.12131. Epub 2015 Mar 1.

PMID:
25727456
38.

Using multiple regression, Bayesian networks and artificial neural networks for prediction of total egg production in European quails based on earlier expressed phenotypes.

Felipe VP, Silva MA, Valente BD, Rosa GJ.

Poult Sci. 2015 Apr;94(4):772-80. doi: 10.3382/ps/pev031. Epub 2015 Feb 22.

PMID:
25713397
39.

Effect of genotype imputation on genome-enabled prediction of complex traits: an empirical study with mice data.

Felipe VP, Okut H, Gianola D, Silva MA, Rosa GJ.

BMC Genet. 2014 Dec 29;15:149. doi: 10.1186/s12863-014-0149-9.

40.

Maternal nutrition induces gene expression changes in fetal muscle and adipose tissues in sheep.

Peñagaricano F, Wang X, Rosa GJ, Radunz AE, Khatib H.

BMC Genomics. 2014 Nov 28;15:1034. doi: 10.1186/1471-2164-15-1034.

41.

One hundred years of statistical developments in animal breeding.

Gianola D, Rosa GJ.

Annu Rev Anim Biosci. 2015;3:19-56. doi: 10.1146/annurev-animal-022114-110733. Epub 2014 Nov 3. Review.

PMID:
25387231
42.

Assessment of respiratory muscle strength in children according to the classification of body mass index.

da Rosa GJ, Schivinski CI.

Rev Paul Pediatr. 2014 Jun;32(2):250-5. English, Portuguese.

43.

Meta-analysis of candidate gene effects using bayesian parametric and non-parametric approaches.

Wu XL, Gianola D, Rosa GJ, Weigel KA.

J Genomics. 2014 Jan 2;2:1-19. doi: 10.7150/jgen.5054. eCollection 2014.

44.

Quantitative genetic study of age at subsequent rebreeding in Nellore cattle by using survival analysis.

Van Melis MH, Figueiredo LG, Oliveira HN, Eler JP, Rosa GJ, Santana ML Jr, Rezende FM, Ferraz JB.

Genet Mol Res. 2014 May 30;13(2):4071-82. doi: 10.4238/2014.May.30.2.

45.

Dissection of additive genetic variability for quantitative traits in chickens using SNP markers.

Abdollahi-Arpanahi R, Pakdel A, Nejati-Javaremi A, Moradi Shahrbabak M, Morota G, Valente BD, Kranis A, Rosa GJ, Gianola D.

J Anim Breed Genet. 2014 Jun;131(3):183-93. doi: 10.1111/jbg.12079. Epub 2014 Jan 25.

PMID:
24460953
46.

Exploring causal networks of bovine milk fatty acids in a multivariate mixed model context.

Bouwman AC, Valente BD, Janss LL, Bovenhuis H, Rosa GJ.

Genet Sel Evol. 2014 Jan 17;46:2. doi: 10.1186/1297-9686-46-2.

47.

Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens.

Abdollahi-Arpanahi R, Nejati-Javaremi A, Pakdel A, Moradi-Shahrbabak M, Morota G, Valente BD, Kranis A, Rosa GJ, Gianola D.

J Anim Breed Genet. 2014 Apr;131(2):123-33. doi: 10.1111/jbg.12075. Epub 2014 Jan 8.

PMID:
24397350
48.

Liver functional genomics in beef cows on grazing systems: novel genes and pathways revealed.

Laporta J, Rosa GJ, Naya H, Carriquiry M.

Physiol Genomics. 2014 Feb 15;46(4):138-47. doi: 10.1152/physiolgenomics.00120.2013. Epub 2013 Dec 10.

PMID:
24326346
49.

Estradiol and progesterone exhibit similar patterns of hepatic gene expression regulation in the bovine model.

Piccinato CA, Rosa GJ, N'jai AU, Jefcoate CR, Wiltbank MC.

PLoS One. 2013 Sep 17;8(9):e73552. doi: 10.1371/journal.pone.0073552. eCollection 2013.

50.

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows.

Savegnago RP, Rosa GJ, Valente BD, Herrera LG, Carneiro RL, Sesana RC, El Faro L, Munari DP.

J Dairy Sci. 2013;96(11):7284-93. doi: 10.3168/jds.2013-6708. Epub 2013 Sep 18.

PMID:
24054283

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