tyna

tyna analyzes, compares, and mines directed and undirected biological interaction networks to characterize network topology and identify motifs, hubs, and bottlenecks for systems biology research.

Key Features:

• Supported network types: Handles both directed and undirected molecular interaction networks.
• Network management: Organizes multiple private and public networks using a flexible tagging system.
• Comparative analysis: Compares networks to reveal structural similarities and differences.
• Mining capabilities: Mines networks for specified patterns and substructures using implemented analytical methods.
• Defective clique identification: Detects subnetworks that are missing certain connections but otherwise form a clique structure.
• Motif detection: Identifies recurring small network motifs, including feed-forward loops.
• Global statistics: Computes topology metrics such as clustering coefficient and eccentricity.
• Hubs and bottlenecks: Identifies key nodes critical for network integrity and information flow.
• Standardized datasets: Includes pre-loaded, categorized datasets for comparative and exploratory analyses.
• Cytoscape integration: Integrates with Cytoscape via a plugin for interoperability with existing network-analysis workflows.

Scientific Applications:

• Systems biology: Characterizes complex molecular interaction networks to support systems-level investigation of biological processes.
• Molecular interaction analysis: Analyzes networks derived from large-scale experiments and curation efforts to elucidate interaction patterns.
• Comparative network genomics: Enables cross-organism comparison of cellular networks to identify conserved and divergent features.

Methodology:

Uses network-analysis techniques explicitly including identification of defective cliques, detection of small network motifs (e.g., feed-forward loops), calculation of global statistics such as clustering coefficient and eccentricity, and identification of hubs and bottlenecks.