TExCNN: Leveraging Pre-Trained Models to Predict Gene Expression from Genomic Sequences.
Journal:
Genes
PMID:
39766860
Abstract
BACKGROUND/OBJECTIVES: Understanding the relationship between DNA sequences and gene expression levels is of significant biological importance. Recent advancements have demonstrated the ability of deep learning to predict gene expression levels directly from genomic data. However, traditional methods are limited by basic word encoding techniques, which fail to capture the inherent features and patterns of DNA sequences.