GeneZip: Region-Aware Compression for Long Context DNA Modeling

GeneZip is a new DNA compression model that achieves 137.6x compression with minimal performance loss by recognizing that genomic information is highly imbalanced. The system enables training of much larger AI models for genomic analysis using single GPU setups instead of expensive multi-GPU configurations.

• →GeneZip achieves 137.6x compression of genomic data with only 0.31 perplexity increase by focusing on information-dense coding regions.
• →The model enables training 82.6x larger models compared to previous state-of-the-art while using only a single A100 GPU.
• →GeneZip supports 636M-parameter models at 1M base pair context, dramatically reducing computational requirements for genome-scale AI.
• →The system matches or exceeds performance on key genomic prediction tasks including contact mapping and gene expression analysis.
• →This breakthrough makes large-scale genomic AI accessible without expensive multi-GPU infrastructure requirements.