LoopDetect

LoopDetect detects feedback loops in ordinary differential equation (ODE) models to identify positive and negative regulatory circuits that influence system stability and dynamic behavior.

Key Features:

• Feedback loop detection: Identifies cycles or circuits representing positive and negative feedback between species (nodes) in ODE models.
• Multi-language implementations: Provides implementations in MATLAB, Python, and R for analysis of ODE models.
• Parameter-range analysis: Supports detection of feedback loops across specified ranges of parameter values.
• User-defined model parameters and states: Accepts user-defined model parametrizations and variable states for analysis.
• Flexible output formats: Generates outputs in formats suitable for downstream analysis.

Scientific Applications:

• Systems biology: Identifies feedback mechanisms to interpret regulatory network structure in systems biology and bioinformatics.
• Regulatory network analysis: Detects positive and negative loops relevant to gene regulation and metabolic pathway control.
• Dynamic behavior and stability assessment: Provides information on stability, robustness, and dynamic properties of biological models.

Methodology:

Analyzes ODE models by examining their mathematical structure and the interactions defined within the model to identify cycles (feedback loops) between species, considering user-defined parameters and variable states.