rsbml

rsbml provides SBML parsing, validation, an S4-based SBML DOM for programmatic model manipulation in R, conversion to R graph objects for network analysis, and optional integration with the SBML ODE Solver Library (SOSLib) for time-course simulations to support pathway and systems biology analyses.

Key Features:

• SBML Parsing and Validation: Parses SBML files and performs validation to verify model correctness within R.
• S4 SBML DOM: Exposes an S4-based Document Object Model (DOM) for structured programmatic access to SBML model components.
• Graph Conversion: Converts SBML models into R graph objects to enable network and pathway analysis.
• Simulation Capabilities (SOSLib): Optionally links with the SBML ODE Solver Library (SOSLib) to run ODE-based time-course simulations.
• Integration and Visualization Support: Integrates with other R packages to support visualization and downstream pathway analyses.

Scientific Applications:

• Network Reconstruction and Pathway Analysis: Facilitates reconstruction and analysis of biological pathways using SBML-encoded models.
• Gene Regulatory Network Analysis: Supports analysis of gene regulatory networks through model manipulation and graph-based methods.
• Metabolic Pathway Simulation: Enables simulation of metabolic pathways via ODE solvers when SOSLib is linked.
• High-Throughput Data Integration: Provides a framework to incorporate pathway knowledge into analyses of high-throughput datasets.
• Contextualizing Findings to Improve Algorithms: Allows incorporation of existing pathway and literature knowledge to enhance algorithm performance and stability.

Methodology:

rsbml implements SBML file parsing and validation, an S4-based SBML DOM for model manipulation, conversion of SBML into R graph objects, optional linkage to SOSLib for ODE time-course simulation, and data import strategies that accommodate external tools and datasets while integrating with other R packages for visualization.