Danilo Hottis-Lyra

NameDanilo Hottis-Lyra
Job titlePost Doctoral Research Scientist - Statistical Genomics
Email addressdanilo.hottis-lyra@rothamsted.ac.uk
DepartmentComputational and Analytical Sciences
ORCIDhttps://orcid.org/0000-0002-2214-1555
Preferred citationLyra, D. H.
OfficeHarpenden

Research outputs

Bayesian analysis and prediction of hybrid performance

Alves, F. C., Granato, I. S. C., Galli, g, Lyra, D. H., Fritsche-Neto, R. and De los Campos, G. 2019. Bayesian analysis and prediction of hybrid performance. Plant Methods. 15, p. 14.

Modeling copy number variation in the genomic prediction of maize hybrids

Lyra, D. H., Galli, G., Alves, F. C., Granato, I. S. C., Vidotti, M. S., Sousa, M. B., Morosini, J. S., Crossa, J. and Fritsche-Neto, R. 2019. Modeling copy number variation in the genomic prediction of maize hybrids. Theoretical and Applied Genetics. 132, pp. 273-288.

Controlling population structure in the genomic prediction of tropical maize hybrids

Lyra, D. H., Granato, Morais, P. P. P., Alves, F. C., Santos, A. R. M., Yu, X., Guo, T., Yu, J. and Fritsche-Neto, R. 2018. Controlling population structure in the genomic prediction of tropical maize hybrids. Molecular Breeding. 38 (126).

Impact of Phenotypic Correction Method and Missing Phenotypic Data on Genomic Prediction of Maize Hybrids

Galli, G, Lyra, D. H., Alves, F. C, Granato, I. S. C., Bandeira-Sousa, M. and Fritsche-Neto, R 2018. Impact of Phenotypic Correction Method and Missing Phenotypic Data on Genomic Prediction of Maize Hybrids. Crop Science. 58 (4), pp. 1481-1491.

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