SMGen

SMGen generates synthetic models of biochemical reaction networks, producing Reaction-based Models (RBMs) for benchmarking computational performance and studying system connectivity and emergent dynamics.

Key Features:

• Automated Model Generation: Automates creation of synthetic models with system connectivity and reaction discreteness that exhibit non-trivial emergent dynamics.
• Graph-Based Framework: Constructs models from an undirected graph with a single connected component to represent network structure.
• Main-Worker Paradigm: Uses a Main-Worker parallel processing paradigm to reduce execution time during model generation.
• Performance Analysis: Generates batches of symmetric and asymmetric RBMs of varying sizes to evaluate how numbers of reactions and species affect generation time.
• Error Handling and Scalability: Detects and corrects errors when the number of reactions exceeds the number of species and can generate models with up to 512 species and reactions in under seven seconds.

Scientific Applications:

• Benchmarking in Computational Systems Biology: Provides synthetic RBMs for assessing simulator and algorithm performance.
• Network Dynamics Research: Supplies models to study system connectivity and emergent behaviors in biochemical reaction networks.
• Parameter Impact Studies: Enables analysis of how varying numbers of species and reactions influence network behavior and computational cost.

Methodology:

Models are generated from an undirected graph ensuring a single connected component; batches of symmetric and asymmetric RBMs are produced and processed using a Main-Worker parallel paradigm, with error detection and correction when reactions exceed species.