This website is a project for analysis of the Genomic Selection for Drought Tolerance Using Genome Wide GBS and/or DART in Cassava by EMBRAPA Mandioca.
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Updated
Oct 27, 2023 - R
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gblup
Here are 4 public repositories matching this topic...
Role of genomics on regulating rice grain metabolic variability under warmer nights: A statistical and image-based deep learning approach
deep-learning
neural-network
bayesian-methods
metabolomics
cnn-keras
genomic-prediction
metabolomics-pipeline
factorial-analysis
heritability-estimation
multi-omic
gblup
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Updated
Nov 6, 2024 - R
Solves kernel ridge regression within the the mixed model framework. All the estimated components and parameters, e.g. BLUP of dual variables and BLUP of random predictor effects for the linear kernel (also known as RR-BLUP), are available.
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Updated
Nov 27, 2024 - R
Evaluating metabolic and genomic data for predicting grain traits under high night temperature stress in rice
machine-learning
random-forest
svm
cross-validation
data-visualization
bayesian-methods
xgboost
classification
multi-omics
multi-trait-analysis
genomic-prediction
gblup
high-night-temperature
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Updated
Apr 2, 2023 - R
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