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Items: 1 to 50 of 257

1.

Including Phenotypic Causal Networks in Genome-Wide Association Studies Using Mixed Effects Structural Equation Models.

Momen M, Ayatollahi Mehrgardi A, Amiri Roudbar M, Kranis A, Mercuri Pinto R, Valente BD, Morota G, Rosa GJM, Gianola D.

Front Genet. 2018 Oct 9;9:455. doi: 10.3389/fgene.2018.00455. eCollection 2018.

2.

Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.

Montesinos-López OA, Montesinos-López A, Crossa J, Gianola D, Hernández-Suárez CM, Martín-Vallejo J.

G3 (Bethesda). 2018 Dec 10;8(12):3829-3840. doi: 10.1534/g3.118.200728.

3.

Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture.

Montesinos-López A, Montesinos-López OA, Gianola D, Crossa J, Hernández-Suárez CM.

G3 (Bethesda). 2018 Dec 10;8(12):3813-3828. doi: 10.1534/g3.118.200740.

4.

Predictive ability of genome-assisted statistical models under various forms of gene action.

Momen M, Mehrgardi AA, Sheikhi A, Kranis A, Tusell L, Morota G, Rosa GJM, Gianola D.

Sci Rep. 2018 Aug 17;8(1):12309. doi: 10.1038/s41598-018-30089-2.

5.

Conceptual framework for investigating causal effects from observational data in livestock.

Bello NM, Ferreira VC, Gianola D, Rosa GJM.

J Anim Sci. 2018 Sep 29;96(10):4045-4062. doi: 10.1093/jas/sky277. Review.

PMID:
30107524
6.

Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

González-Camacho JM, Ornella L, Pérez-Rodríguez P, Gianola D, Dreisigacker S, Crossa J.

Plant Genome. 2018 Jul;11(2). doi: 10.3835/plantgenome2017.11.0104.

7.

Prediction of Complex Traits: Robust Alternatives to Best Linear Unbiased Prediction.

Gianola D, Cecchinato A, Naya H, Schön CC.

Front Genet. 2018 Jun 5;9:195. doi: 10.3389/fgene.2018.00195. eCollection 2018.

8.

Transmission scanning electron microscopy: Defect observations and image simulations.

Callahan PG, Stinville JC, Yao ER, Echlin MP, Titus MS, De Graef M, Gianola DS, Pollock TM.

Ultramicroscopy. 2018 Mar;186:49-61. doi: 10.1016/j.ultramic.2017.11.004. Epub 2017 Dec 6.

PMID:
29268135
9.

Structure-property relationships from universal signatures of plasticity in disordered solids.

Cubuk ED, Ivancic RJS, Schoenholz SS, Strickland DJ, Basu A, Davidson ZS, Fontaine J, Hor JL, Huang YR, Jiang Y, Keim NC, Koshigan KD, Lefever JA, Liu T, Ma XG, Magagnosc DJ, Morrow E, Ortiz CP, Rieser JM, Shavit A, Still T, Xu Y, Zhang Y, Nordstrom KN, Arratia PE, Carpick RW, Durian DJ, Fakhraai Z, Jerolmack DJ, Lee D, Li J, Riggleman R, Turner KT, Yodh AG, Gianola DS, Liu AJ.

Science. 2017 Nov 24;358(6366):1033-1037. doi: 10.1126/science.aai8830.

10.

It is unlikely that genomic selection will ever be 100% accurate.

Gianola D.

J Anim Breed Genet. 2017 Dec;134(6):438-440. doi: 10.1111/jbg.12307. No abstract available.

PMID:
29164759
11.

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.

12.

Efficacy of pasireotide in controlling severe hypercortisolism until cardiac transplantation.

Attanasio R, Cortesi L, Gianola D, Vettori C, Sileo F, Trevisan R.

Endocrinol Diabetes Metab Case Rep. 2017 Mar 8;2017. pii: 16-0140. doi: 10.1530/EDM-16-0140. eCollection 2017.

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.

Assessing genomic prediction accuracy for Holstein sires using bootstrap aggregation sampling and leave-one-out cross validation.

Mikshowsky AA, Gianola D, Weigel KA.

J Dairy Sci. 2017 Jan;100(1):453-464. doi: 10.3168/jds.2016-11496. Epub 2016 Nov 23.

PMID:
27889124
17.

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
18.

High-strength magnetically switchable plasmonic nanorods assembled from a binary nanocrystal mixture.

Zhang M, Magagnosc DJ, Liberal I, Yu Y, Yun H, Yang H, Wu Y, Guo J, Chen W, Shin YJ, Stein A, Kikkawa JM, Engheta N, Gianola DS, Murray CB, Kagan CR.

Nat Nanotechnol. 2017 Mar;12(3):228-232. doi: 10.1038/nnano.2016.235. Epub 2016 Nov 7.

PMID:
27819691
19.

Genome-Wide Association Studies with a Genomic Relationship Matrix: A Case Study with Wheat and Arabidopsis.

Gianola D, Fariello MI, Naya H, Schön CC.

G3 (Bethesda). 2016 Oct 13;6(10):3241-3256. doi: 10.1534/g3.116.034256.

20.

Cross-Validation Without Doing Cross-Validation in Genome-Enabled Prediction.

Gianola D, Schön CC.

G3 (Bethesda). 2016 Oct 13;6(10):3107-3128. doi: 10.1534/g3.116.033381.

21.

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.

22.

Linking stress-driven microstructural evolution in nanocrystalline aluminium with grain boundary doping of oxygen.

He MR, Samudrala SK, Kim G, Felfer PJ, Breen AJ, Cairney JM, Gianola DS.

Nat Commun. 2016 Apr 13;7:11225. doi: 10.1038/ncomms11225.

23.

Improving reliability of genomic predictions for Jersey sires using bootstrap aggregation sampling.

Mikshowsky AA, Gianola D, Weigel KA.

J Dairy Sci. 2016 May;99(5):3632-3645. doi: 10.3168/jds.2015-10715. Epub 2016 Mar 9.

PMID:
26971146
24.

Genome-enabled prediction using probabilistic neural network classifiers.

González-Camacho JM, Crossa J, Pérez-Rodríguez P, Ornella L, Gianola D.

BMC Genomics. 2016 Mar 9;17:208. doi: 10.1186/s12864-016-2553-1.

25.

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.

26.

Thermomechanical Behavior of Molded Metallic Glass Nanowires.

Magagnosc DJ, Chen W, Kumar G, Schroers J, Gianola DS.

Sci Rep. 2016 Jan 20;6:19530. doi: 10.1038/srep19530.

27.

Orthogonal Control of Stability and Tunable Dry Adhesion by Tailoring the Shape of Tapered Nanopillar Arrays.

Cho Y, Kim G, Cho Y, Lee SY, Minsky H, Turner KT, Gianola DS, Yang S.

Adv Mater. 2015 Dec 16;27(47):7788-93. doi: 10.1002/adma.201503347. Epub 2015 Oct 21.

PMID:
26488215
28.

Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens.

Beissinger TM, Gholami M, Erbe M, Weigend S, Weigend A, de Leon N, Gianola D, Simianer H.

Heredity (Edinb). 2016 Feb;116(2):158-66. doi: 10.1038/hdy.2015.81. Epub 2015 Sep 9.

29.

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.

30.

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.

31.

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.

32.

Do Molecular Markers Inform About Pleiotropy?

Gianola D, de los Campos G, Toro MA, Naya H, Schön CC, Sorensen D.

Genetics. 2015 Sep;201(1):23-9. doi: 10.1534/genetics.115.179978. Epub 2015 Jul 23.

33.

Nanomechanics: Full recovery takes time.

Gianola DS, Shin J.

Nat Nanotechnol. 2015 Aug;10(8):659-60. doi: 10.1038/nnano.2015.164. Epub 2015 Jul 13. No abstract available.

PMID:
26167764
34.

Measuring surface dislocation nucleation in defect-scarce nanostructures.

Chen LY, He MR, Shin J, Richter G, Gianola DS.

Nat Mater. 2015 Jul;14(7):707-13. doi: 10.1038/nmat4288. Epub 2015 May 18.

PMID:
25985457
35.

Genomic heritability: what is it?

de Los Campos G, Sorensen D, Gianola D.

PLoS Genet. 2015 May 5;11(5):e1005048. doi: 10.1371/journal.pgen.1005048. eCollection 2015 May.

36.

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.

37.

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.

38.

Application of neural networks with back-propagation to genome-enabled prediction of complex traits in Holstein-Friesian and German Fleckvieh cattle.

Ehret A, Hochstuhl D, Gianola D, Thaller G.

Genet Sel Evol. 2015 Mar 31;47:22. doi: 10.1186/s12711-015-0097-5.

39.

A robust smart window: reversibly switching from high transparency to angle-independent structural color display.

Ge D, Lee E, Yang L, Cho Y, Li M, Gianola DS, Yang S.

Adv Mater. 2015 Apr 17;27(15):2489-95. doi: 10.1002/adma.201500281. Epub 2015 Mar 2.

PMID:
25732127
40.

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
41.

Bayesian analysis of additive epistasis arising from new mutations in mice.

Casellas J, Gianola D, Medrano JF.

Genet Res (Camb). 2014 Aug 13;96:e008. doi: 10.1017/S001667231400010X.

PMID:
25578900
42.

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.

43.

Robust scaling of strength and elastic constants and universal cooperativity in disordered colloidal micropillars.

Strickland DJ, Huang YR, Lee D, Gianola DS.

Proc Natl Acad Sci U S A. 2014 Dec 23;111(51):18167-72. doi: 10.1073/pnas.1413900111. Epub 2014 Dec 8.

44.

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
45.

Kernel-based whole-genome prediction of complex traits: a review.

Morota G, Gianola D.

Front Genet. 2014 Oct 16;5:363. doi: 10.3389/fgene.2014.00363. eCollection 2014. Review.

46.

Bayesian genomic-enabled prediction as an inverse problem.

Cuevas J, Pérez-Elizalde S, Soberanis V, Pérez-Rodríguez P, Gianola D, Crossa J.

G3 (Bethesda). 2014 Aug 25;4(10):1991-2001. doi: 10.1534/g3.114.013094.

47.

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.

48.

Tailoring and understanding the mechanical properties of nanoparticle-shelled bubbles.

Brugarolas T, Gianola DS, Zhang L, Campbell GM, Bassani JL, Feng G, Lee D.

ACS Appl Mater Interfaces. 2014 Jul 23;6(14):11558-72. doi: 10.1021/am502290h. Epub 2014 Jul 3.

PMID:
24956417
49.

Strain- and defect-mediated thermal conductivity in silicon nanowires.

Murphy KF, Piccione B, Zanjani MB, Lukes JR, Gianola DS.

Nano Lett. 2014 Jul 9;14(7):3785-92. doi: 10.1021/nl500840d. Epub 2014 Jun 9.

PMID:
24885097
50.

Whole genome prediction of bladder cancer risk with the Bayesian LASSO.

de Maturana EL, Chanok SJ, Picornell AC, Rothman N, Herranz J, Calle ML, García-Closas M, Marenne G, Brand A, Tardón A, Carrato A, Silverman DT, Kogevinas M, Gianola D, Real FX, Malats N.

Genet Epidemiol. 2014 Jul;38(5):467-76. doi: 10.1002/gepi.21809. Epub 2014 May 5.

PMID:
24796258

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