[HTML][HTML] Comparison of omics technologies for hybrid prediction
M Westhues - 2020 - opus.uni-hohenheim.de
One of the great challenges for plant breeders is dealing with the vast number of putative
candidates, which cannot be tested exhaustively in multi-environment field trials. Using …
candidates, which cannot be tested exhaustively in multi-environment field trials. Using …
Omics-based hybrid prediction in maize
M Westhues, TA Schrag, C Heuer, G Thaller… - Theoretical and applied …, 2017 - Springer
Key message Complementing genomic data with other “omics” predictors can increase the
probability of success for predicting the best hybrid combinations using complex agronomic …
probability of success for predicting the best hybrid combinations using complex agronomic …
Incorporation of trait-specific genetic information into genomic prediction models
Due to the rapid development of high-throughput sequencing technology, we can easily
obtain not only the genetic variants at the whole-genome sequence level (eg, from 1000 …
obtain not only the genetic variants at the whole-genome sequence level (eg, from 1000 …
Genome-enabled prediction using probabilistic neural network classifiers
Background Multi-layer perceptron (MLP) and radial basis function neural networks
(RBFNN) have been shown to be effective in genome-enabled prediction. Here, we …
(RBFNN) have been shown to be effective in genome-enabled prediction. Here, we …
Extend mixed models to multilayer neural networks for genomic prediction including intermediate omics data
With the growing amount and diversity of intermediate omics data complementary to
genomics (eg DNA methylation, gene expression, and protein abundance), there is a need …
genomics (eg DNA methylation, gene expression, and protein abundance), there is a need …
[PDF][PDF] Quantitative basis of machine learning models for genomic prediction
C Syrowatka, N Machnik, MR Robinson - researchgate.net
However, despite this immense body of data and its implication for human health, reliable
prediction of an individual's risk for heritable diseases remains limited. Non-additive genetic …
prediction of an individual's risk for heritable diseases remains limited. Non-additive genetic …
A guidance of model selection for genomic prediction based on linear mixed models for complex traits
J Duan, J Zhang, L Liu, Y Wen - Frontiers in Genetics, 2022 - frontiersin.org
Brain imaging outcomes are important for Alzheimer's disease (AD) detection, and their
prediction based on both genetic and demographic risk factors can facilitate the ongoing …
prediction based on both genetic and demographic risk factors can facilitate the ongoing …
Adding gene transcripts into genomic prediction improves accuracy and reveals sampling time dependence
BC Perez, MCAM Bink, KL Svenson, GA Churchill… - G3, 2022 - academic.oup.com
Recent developments allowed generating multiple high-quality 'omics' data that could
increase the predictive performance of genomic prediction for phenotypes and genetic merit …
increase the predictive performance of genomic prediction for phenotypes and genetic merit …
Usefulness of Multiparental Populations of Maize (Zea mays L.) for Genome-Based Prediction
The efficiency of marker-assisted prediction of phenotypes has been studied intensively for
different types of plant breeding populations. However, one remaining question is how to …
different types of plant breeding populations. However, one remaining question is how to …
Building a calibration set for genomic prediction, characteristics to be considered, and optimization approaches
S Rio, A Charcosset, T Mary-Huard, L Moreau… - Genomic prediction of …, 2022 - Springer
The efficiency of genomic selection strongly depends on the prediction accuracy of the
genetic merit of candidates. Numerous papers have shown that the composition of the …
genetic merit of candidates. Numerous papers have shown that the composition of the …