Learning Structurally Stabilized Representations for Multi-modal
Lossless DNA Storage
Learning Structurally Stabilized Representations for Multi-modal
Lossless DNA Storage
In this paper, we present Reed-Solomon coded single-stranded representation learning (RSRL), a novel end-to-end model for learning representations for multi-modal lossless DNA storage. In contrast to existing learning-based methods, the proposed RSRL is inspired by both error-correction codec and structural biology. Specifically, RSRL first learns the representations for the subsequent …