SBMLsqueezer

SBMLsqueezer automates generation of kinetic rate laws for reactions in SBML biochemical network models to enable construction of large-scale kinetic models and integration with experimentally-derived kinetics from SABIO-RK.

Key Features:

• Automated rate law generation: Automatically suggests and generates kinetic rate laws for each reaction in a biochemical network model.
• High-throughput algorithm: Implements a high-throughput algorithm scalable to large network reconstructions.
• Reaction-type criteria: Applies predefined criteria based on reaction types to select appropriate rate laws.
• SABIO-RK integration: Retrieves experimentally-derived rate laws from the SABIO-RK kinetics database for parameterization or substitution.
• Configurable selection: Allows specification of selection criteria or experimental context to influence rate law choice.

Scientific Applications:

• Large-scale kinetic model construction: Enables automated assignment of rate laws to build accurate kinetic models of biochemical networks.
• Integration with experimental data: Grounds computational kinetic models in experimentally-derived rate laws from SABIO-RK.
• Systems biology workflows: Accelerates systems biology and related computational modeling workflows by reducing manual rate-law assignment.

Methodology:

Uses a high-throughput algorithm to suggest and generate rate laws for each reaction based on predefined reaction-type criteria and optionally retrieves experimentally-derived rate laws from the SABIO-RK database.