A sequence knowledge-guided deep learning method for single-cell multi-omics translation

Key Points

• The aim is to enhance multi-omics integration by creating a sequence-aware framework for cross-modal translation.
• Developed a modular architecture for multi-omics integration
• Introduced a sequence-aware paradigm
• Enabled zero-shot capability for application flexibility
• Improved data acquisition for proteome analysis
• Facilitated the integration of single-cell multi-omics data
• Showed robustness across various omics technologies

Abstract