SNAVI

SNAVI analyzes and visualizes biological signaling networks to support topological and statistical investigation of protein-protein and ligand-protein interactions.

Key Features:

• Graph Representation: Represents protein-protein and ligand-protein interactions as graphs with biomolecules as nodes and interactions as links.
• Network Metrics: Computes clustering coefficients and connectivity distributions for network topological characterization.
• Network Motif Detection: Detects network motifs within signaling networks.
• Visualization: Visualizes large-scale signaling networks to display complex interaction structures.
• Data Integration: Integrates experimental data from various sources into network representations.
• Import and Export: Constructs networks from lists of gene or protein names and generates linked web pages from text-formatted network datasets.

Scientific Applications:

• Topological Analysis of Signaling Networks: Enables topological and statistical analysis of large-scale cell signaling networks to study signal transduction interactions.
• Pathway Interaction Exploration: Supports exploration of how signal transduction pathways interact to form complex interaction networks.
• Therapeutic Target Identification: Facilitates identification of candidate therapeutic targets through analysis of network topology and motifs.

Methodology:

Represents interactions as graphs (nodes=biomolecules, links=interactions), computes clustering coefficients and connectivity distributions, detects network motifs, constructs networks from gene/protein name lists, ingests text-formatted network datasets and generates linked web pages, integrates experimental data from various sources, and visualizes resulting networks.