Bioinformatics & AI bridges the gap between life sciences and intelligent computation. As biological datasets grow exponentially — from whole-genome sequencing to single-cell transcriptomics — AI methods become essential for extracting knowledge from complexity.

The journal publishes original research on machine learning for genomics, protein structure prediction, drug discovery, medical imaging, and AI-driven analysis of biological data.

Scope includes:

• Deep learning for genomics, proteomics, and metabolomics
• AI-assisted drug discovery and molecular design
• Protein structure and function prediction
• Medical image analysis and computational pathology
• NLP for biomedical literature
• Graph neural networks for molecular and biological networks
• Foundation models for biological sequences
• Explainable AI in healthcare and diagnostics
• Federated learning and privacy-preserving methods in biomedicine
• AI for epidemiology and public health modeling

All submissions undergo rigorous double-blind peer review. Published articles receive a Crossref DOI and are immediately available under open access.