Results 11 to 20 of about 3,400,423 (242)

Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project

Frontiers in Genetics, 2021
Genomic prediction provides an efficient alternative to conventional phenotypic selection for developing improved cultivars with desirable characteristics.
D. Jarquín, Natalia de León, C. Romay, M. Bohn, E. Buckler, I. Ciampitti, J. Edwards, D. Ertl, S. Flint-Garcia, M. Gore, Christopher Graham, C. Hirsch, J. Holland, D. Hooker, S. Kaeppler, J. Knoll, Elizabeth C. Lee, Carolyn J. Lawrence-Dill, J. Lynch, S. Moose, S. Murray, R. Nelson, T. Rocheford, James c. Schnable, P. Schnable, Margaret E. Smith, Nathan M. Springer, P. Thomison, M. Tuinstra, R. Wisser, Wenwei Xu, Jianming Yu, A. Lorenz   +32 more
semanticscholar   +1 more source

Environment-specific genomic prediction ability in maize using environmental covariates depends on environmental similarity to training data.

G3, 2021
Technology advances have made possible the collection of a wealth of genomic, environmental, and phenotypic data for use in plant breeding. Incorporation of environmental data into environment-specific genomic prediction is hindered in part because of ...
A. R. Rogers, J. Holland
semanticscholar   +1 more source

Strategies to improve the accuracy and reduce costs of genomic prediction in aquaculture species

Evolutionary Applications, 2021
Genomic selection (GS) has great potential to increase genetic gain in aquaculture breeding; however, its implementation is hindered owing to high genotyping cost and the large number of individuals to genotype.
Hailiang Song, Hongxia Hu
semanticscholar   +1 more source

Estimation of Pool Construction and Technical Error

Agriculture, 2021
Pooling animals with extreme phenotypes can improve the accuracy of genetic evaluation or provide genetic evaluation for novel traits at relatively low cost by exploiting large amounts of low-cost phenotypic data from animals in the commercial sector ...
John Keele, Tara McDaneld, Ty Lawrence, Jenny Jennings, Larry Kuehn   +4 more
doaj   +1 more source

Genomics-aided structure prediction [PDF]

Proceedings of the National Academy of Sciences, 2012
We introduce a theoretical framework that exploits the ever-increasing genomic sequence information for protein structure prediction. Structure-based models are modified to incorporate constraints by a large number of non-local contacts estimated from direct coupling analysis (DCA) of co-evolving genomic sequences.
Sulkowska, Joanna I., Morcos, Faruck, Weigt, Martin, Hwa, Terence, Onuchic, Jose N.   +4 more
openaire   +3 more sources

Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects

Theoretical and Applied Genetics, 2021
Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. In the recent
S. Yadav, Xianming Wei, P. Joyce, F. Atkin, E. Deomano, Yue Sun, L. Nguyen, E. Ross, Tony Cavallaro, K. Aitken, B. Hayes, K. Voss-Fels   +11 more
semanticscholar   +1 more source

Genomic Prediction: Progress and Perspectives for Rice Improvement. [PDF]

Methods in molecular biology, 2021
Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy.
J. Bartholomé, P. Prakash, J. Cobb
semanticscholar   +1 more source

Genomic prediction using subsampling [PDF]

BMC Bioinformatics, 2017
Genome-wide assisted selection is a critical tool for the genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov
Alencar Xavier, William M. Muir, Katy M. Rainey, Shizhong Xu   +3 more
openaire   +3 more sources

Application of Genomic Data for Reliability Improvement of Pig Breeding Value Estimates

Animals, 2021
Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best ...
Ekaterina Melnikova, Artem Kabanov, Sergey Nikitin, Maria Somova, Sergey Kharitonov, Petr Otradnov, Olga Kostyunina, Tatiana Karpushkina, Elena Martynova, Aleksander Sermyagin, Natalia Zinovieva   +10 more
doaj   +1 more source

Random Forest for Genomic Prediction

Multivariate Statistical Machine Learning Methods for Genomic Prediction, 2022
We give a detailed description of random forest and exemplify its use with data from plant breeding and genomic selection. The motivations for using random forest in genomic-enabled prediction are explained.
O. A. Montesinos López, Abelardo Montesinos López, J. Crossa   +2 more
semanticscholar   +1 more source