CINNA

CINNA performs centrality analysis and compares multiple centrality measures across weighted and unweighted, directed and undirected networks to identify the most informative measures using dimensionality-reduction techniques.

Key Features:

• Support for network types: Handles weighted and unweighted as well as directed and undirected network structures.
• Centrality computation: Computes multiple centrality measures to quantify node importance within network topology.
• Comparison and evaluation: Compares and evaluates different centrality measures to assess which best reflect node essentiality.
• Assorting and visualization: Assorts and visualizes various centrality metrics for comparative inspection.
• Dimensionality-reduction: Applies dimensionality-reduction techniques to identify the most informative centrality measures.
• Systematic assessment: Enables systematic assessment of centrality-measure suitability for specific network structures.

Scientific Applications:

• Bioinformatics: Analysis of biological networks to evaluate node importance and essentiality.
• Systems biology: Support for studies relying on network topology to interpret system-level relationships.
• Network analysis: Comparative and interpretative analysis of complex network data using multiple centrality perspectives.

Methodology:

Computational steps include computing multiple centrality measures, comparing and assorting them, visualizing centrality metrics, and applying dimensionality-reduction techniques to identify the most informative measures for weighted/unweighted and directed/undirected networks.