ISMA

ISMA efficiently identifies all occurrences of predefined subgraphs within large networks to enable discovery and analysis of network motifs.

Key Features:

• Tree-Based Algorithm: Employs a tree structure to systematically explore nodes within the query subgraph and optimize the order of investigation.
• Data Structures and Symmetry Exploitation: Leverages specialized data structures and exploits symmetry characteristics inherent in subgraphs to improve efficiency.
• Performance Optimization: Selects the node investigation sequence to achieve notable speedups, particularly on large networks and extensive query subgraphs.

Scientific Applications:

• Network Motif Discovery: Identifies subgraph patterns that occur more frequently than expected by chance for the analysis of network motifs.
• Biological Network Analysis: Facilitates structural and functional analysis of biological networks such as protein-protein interaction networks and gene regulatory networks.

Methodology:

Performs strategic traversal of query subgraph nodes guided by an optimized search tree structure, using specialized data structures and symmetry exploitation to determine node investigation order.