RAGP: a retrieval-augmented deep learning model for genomic prediction in crop breeding

This publication has 28 references indexed in Scilit:

• Genomic selection in plant breeding: Key factors shaping two decades of progress
  Molecular Plant, 2024
• Wheat Yield Prediction Using Machine Learning: A Survey
  2023
• Genomic selection performs as effectively as phenotypic selection for increasing seed yield in soybean
  The Plant Genome, 2022
• DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants
  Molecular Plant, 2022
• Multivariate Statistical Machine Learning Methods for Genomic Prediction
  2022
• Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data
  Journal of Plant Physiology, 2021
• Estimates for World Population and Global Food Availability for Global Health
  2019
• Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values
  2013
• Application of support vector regression to genome-assisted prediction of quantitative traits
  Theoretical and Applied Genetics, 2011
• Wheat genetic resources enhancement by the International Maize and Wheat Improvement Center (CIMMYT)
  Genetic Resources and Crop Evolution, 2008