From single-omics to interactomics: How can ligand-induced perturbations modulate single-cell phenotypes?

Area of Science:

• Cellular biology
• Computational biology
• Pharmacology

Background:

• Cellular perturbations from stimuli, including therapeutic agents, alter cell profiles and functions, potentially impacting tissues.
• External ligand exposure induces changes in cell profiles across various single-omics levels.
• Understanding these molecular changes is vital for assessing therapeutic agent effects.

Purpose of the Study:

• To review recent advances in computational tools for analyzing ligand-induced perturbations using single-cell omics data.
• To discuss the limitations of current computational approaches and data integration methods.
• To explore how large datasets can enhance drug research and development.

Main Methods:

• Single-cell RNA-sequencing (scRNA-seq) for cell profiling and perturbation analysis.
• Integration of single-cell transcriptomics with other omics data (proteomics, epigenomics).
• Focus on computational tools and algorithms for processing and integrating multi-omics data.

Main Results:

• Single-cell omics enables detailed analysis of cellular responses to perturbations.
• Integration of multi-omics data provides a comprehensive view of perturbation mechanisms.
• Advances in computational tools are essential for handling and interpreting complex single-cell data.

Conclusions:

• Computational tools are critical for processing and integrating diverse single-cell omics data.
• Improved analysis of ligand-induced perturbations can accelerate drug discovery and development.
• Addressing current limitations in computational methods is key to leveraging big data in pharmacology.