Single-Cell and Spatial Omics: Methods and Applications

Area of Science:

• Biomedical Research
• Genomics
• Computational Biology

Background:

• Single-cell and spatial omics provide high-resolution molecular profiling, overcoming bulk sequencing limitations.
• These technologies reveal cellular heterogeneity and spatial organization crucial for understanding biology and disease.
• Rapid advancements in high-throughput, subcellular, and multiomics profiling are driving deeper biological insights.

Purpose of the Study:

• To synthesize recent breakthroughs in single-cell and spatial omics technologies.
• To survey computational methods, including AI and foundation models, for analyzing omics data.
• To highlight applications in human health and disease for biomarker discovery and precision medicine.

Main Methods:

• Review of single-cell and spatial omics technologies.
• Survey of computational methods, including AI-driven approaches and multi-omics integration.
• Summarization of applications across human organ systems.

Main Results:

• Significant progress in single-cell and spatial omics technologies and computational analysis methods.
• Demonstrated applications in diverse biological systems and diseases.
• Identified opportunities for biomarker discovery, therapeutic target identification, and precision medicine.

Conclusions:

• A gap exists between technological advancements and their systematic application in human biology and pathology.
• Bridging technological innovation with robust biomedical discovery is crucial for translational impact.
• This review serves as a guide for researchers to accelerate the translation of single-cell and spatial omics.