GeneEx

GeneEx simulates and analyzes gene regulatory circuits (GRCs) using ordinary differential equations (ODEs) to study dynamic behaviors and steady states of genetic networks.

Key Features:

• ODE-based modeling: Uses ordinary differential equations (ODEs) for mathematical modeling of gene regulatory circuits.
• Customizable simulations: Allows variation of parameter ranges, adjustment of gene expression noise levels, and modification of GRC network topology.
• Parameter ensembles: Supports simulations with explicit kinetic parameter sets or large ensembles of randomly generated parameters to probe parameter-dependent behaviors.
• Attractor analysis: Computes the number and stability of attractors to identify potential steady states and dynamic behaviors.
• Data comparison: Compares simulated outputs with uploaded experimental gene expression data for model validation and refinement.
• Curated database: Provides a collection of circuit motifs and known biological GRCs for use in simulations and comparisons.
• Systems-biology analyses: Enables investigation of parameter variation, stochastic effects, and topological changes on gene expression within GRCs.

Scientific Applications:

• GRC dynamics analysis: Investigates time-course behavior and steady states of gene regulatory networks.
• Model validation: Facilitates comparison of simulated outputs to experimental gene expression data for model testing and refinement.
• Parameter sensitivity studies: Explores how variation in kinetic parameters and noise influences network behavior.
• Attractor landscape characterization: Identifies and characterizes attractors to study potential steady states and dynamic regimes of biological systems.

Methodology:

Simulates GRC dynamics using ordinary differential equations (ODEs) with explicit kinetic parameter sets or large ensembles of randomly generated parameters, performs attractor analysis, compares simulated outputs to experimental gene expression data, and supports variation of parameter ranges, gene-expression noise levels, and network topology.