CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants.

Abstract excerpt

Genomic selection leverages genome-wide markers and phenotypes to predict breeding values, with its effectiveness largely dependent on the accuracy of genomic prediction (GP) models. However, GP methods often struggle to capture inter-individual variability and are limited by the curse of dimensionality, where the number of single-nucleotide polymorphisms (SNPs) far exceeds the sample size. To address these...

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