OmicsViz

OmicsViz integrates omics and interaction datasets to support integrative analysis of drug effects and molecular interactions relevant to SARS-CoV-2 and COVID-19 research.

Key Features:

• Integration of Diverse Data Types: Consolidates drug-cell line interference data, virus-host protein-protein interactions, and drug-target interactions into a unified analytical context.
• Visualization of Molecular and Network Data: Generates visual representations of protein networks, drug-target networks, and gene expression changes for molecular-level interpretation.
• Gene Expression Analysis of Drug-Treated Cell Lines: Analyzes gene expression changes in cell lines treated with specific drugs, including examples such as chloroquine and ruxolitinib.
• Drug-Target Network Construction: Constructs drug-target protein networks for anti-coronavirus agents and for drugs interacting with ACE2 to examine potential combinatorial effects with agents like antihistamines or zinc.
• Immune Cell Infiltration Profiling: Profiles immune cell infiltration across COVID-19 patient groups to identify molecular signatures related to immune exhaustion in ICU-admitted and elderly patients.
• Custom Data Input: Accepts user-provided datasets for incorporation into integration, analysis, and visualization workflows.

Scientific Applications:

• Drug Efficacy Evaluation: Enables evaluation of how compounds such as chloroquine and ruxolitinib alter gene expression and potentially modulate immune responses in treated cell lines.
• Network Analysis: Supports exploration of drug-target and virus-host interaction networks for anti-coronavirus drugs and ACE2 interactors to identify potential synergistic interactions.
• Immune Response Profiling: Facilitates comparison of immune cell infiltration profiles among different COVID-19 patient cohorts to reveal mechanisms of immune exhaustion in ICU patients and elderly individuals.

Methodology:

Integrates and visualizes datasets on gene expression, virus-host protein-protein interactions, drug-target interactions, and immune cell dynamics to support analysis of drug–molecular interaction relationships.