Fine-tuning sequence-to-expression models on personal genome and transcriptome data.

Abstract excerpt

BACKGROUND: Genomic sequence-to-expression deep learning models, which are trained to predict gene expression and other molecular phenotypes across the reference genome, have recently been shown to have poor out-of-the-box performance in predicting gene expression variation across individuals based on their personal genome sequences. RESULTS: Here, we explore whether additional training (fine-tuning) on paired...

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