SSBlazer

SSBlazer predicts single-strand break (SSB) sites at nucleotide resolution using a deep learning framework.

Key Features:

• Genome-wide nucleotide-resolution prediction: SSBlazer predicts SSB sites at single-nucleotide resolution across the genome.
• Explainable model: SSBlazer provides an interpretable deep learning framework for understanding SSB predictions.
• Scalable architecture: SSBlazer enables large-scale SSB analysis without the cost of sequencing-based detection methods.
• Cross-species generalization: SSBlazer demonstrates robust generalization capabilities across various species.
• Lightweight design: SSBlazer is a lightweight model suitable for numerous unexplored SSB-related applications.

Scientific Applications:

• Single-strand break site prediction: SSBlazer predicts SSB locations as an alternative to costly sequencing-based detection methods.
• Large-scale SSB analysis: SSBlazer enables genome-wide SSB studies that are unfeasible with experimental sequencing approaches.
• Cross-species SSB research: SSBlazer supports SSB-related applications across multiple species.

Methodology:

SSBlazer utilizes genome-wide single-strand break sequencing data as input for deep learning-based prediction.