Convergence: Multi-omics and AI are reshaping the landscape biomedical research

Area of Science:

• Biomedical research
• Disease mechanisms
• Translational science

Background:

• Convergence of multi-omics, artificial intelligence (AI), and systems biology driving transformative biomedical research.
• Focus on eight thematic sections: cancer, inflammatory/infectious diseases, neurodegeneration, cardiovascular health, autophagy, respiratory disease, and heme biology.
• Exploration of integrative methodologies to simplify complex disease mechanisms.

Discussion:

• Studies discuss biomarker discovery, disease mechanisms, redox biology, lipidomics, machine learning, and proteogenomics in redefining pathophysiological frameworks.
• Examples include spatial omics in colorectal cancer and ferroptosis in asthma/sepsis, showcasing translational power of network analysis.
• Addresses key challenges: standardization, ethical AI integration, and global infrastructure gaps.

Key Insights:

• Integrative methodologies simplify complex disease mechanisms.
• Redox biology, lipidomics, machine learning, and proteogenomics are redefining disease frameworks.
• Network analysis and validation demonstrate translational power in specific disease contexts.

Outlook:

• Roadmap toward precision medicine with tailored diagnostics, therapies, and prognoses.
• Establishes BBA - Molecular Basis of Disease as a platform for next-generation disease biology.
• Highlights innovation in personalized healthcare through molecular individuality.