NetPathMiner

NetPathMiner reconstructs and mines biological pathway networks to identify and prioritize condition-specific active paths across KGML, SBML, and BioPAX datasets.

Key Features:

• Multi-Format Compatibility: Integrates data from KGML, SBML, and BioPAX files for network reconstruction.
• Network Representations: Constructs metabolic, reactiomic, and genic network representations for multifaceted pathway analysis.
• Path Mining and Ranking: Identifies active paths relevant to experimental conditions and ranks them by significance using ranking algorithms.
• Machine Learning Integration: Applies Markov model-based clustering and classification to ranked paths for summarization and categorization of pathways.
• Visualization Capabilities: Produces static and interactive visualizations of networks and paths to support exploration and interpretation.

Scientific Applications:

• Systems Biology Analysis: Analyzes dynamic interactions in genome-scale networks to study system-level behavior.
• Disease Mechanisms and Drug Response: Identifies condition-specific pathways relevant to disease mechanisms and drug response.
• Metabolic Regulation and Interpretation: Detects condition-associated metabolic pathway changes and aids interpretation through visualizations and machine learning summaries.

Methodology:

Constructs networks from KGML, SBML, and BioPAX input files, identifies active paths relevant to experimental conditions, ranks paths for significance, applies Markov model-based clustering and classification to ranked paths, and generates static and interactive visualizations.