CySpanningTree

CySpanningTree computes minimal and maximal spanning trees from Cytoscape networks using Prim's and Kruskal's algorithms to extract subnetworks for network analysis and optimization.

Key Features:

• Algorithms: Supports Prim's and Kruskal's algorithms for computing spanning trees.
• Spanning tree types: Extracts both minimal and maximal spanning trees by selecting edges according to edge weights.
• Cytoscape integration: Operates as an app within Cytoscape to apply spanning tree extraction to Cytoscape network objects.
• Heuristic TSP approximation: Provides an MST-based heuristic to approximate solutions to the traveling salesman problem.
• Data types handled: Applicable to gene expression datasets and global network structures.
• Applications supported: Enables network optimization, cost-effective network design, cluster analysis, and approximation approaches for NP-hard problems.
• Sequencing data reduction: Reduces data complexity and storage requirements for protein and amino acid sequencing tasks.

Scientific Applications:

• Network Optimization: Identifies minimal spanning trees to optimize network design for cost efficiency and performance.
• Data Reduction: Simplifies protein and amino acid sequencing data into subnetworks to reduce storage and complexity.
• Cluster Analysis: Extracts spanning trees to facilitate identification and analysis of clusters within large biological networks such as gene expression networks.
• Approximation Algorithms: Uses MST-based heuristics to provide approximations for NP-hard combinatorial problems like the traveling salesman problem.

Methodology:

Applies Prim's or Kruskal's algorithm to a Cytoscape network to construct a spanning tree (minimal or maximal) by selecting edges based on weight while preventing cycles so that the resulting subnetwork spans all vertices.