SBPD extension package

Category Cross-Omics>Pathway Analysis/Tools

Abstract The SBPD extension package (SBPD) for the Systems Biology Toolbox 2 (see G6G Product Number 20359) adds high-speed simulations, combination of models, experiments, and measurement data in so called 'projects'.

Functions are available that support the complete 'model building' process (modeling, simulation, identifiability analysis, model reduction, parameter estimation (multiple experiment and multiple measurement fitting), validation, etc.).

The projects are an 'advanced construct' that allows you to keep a perfect overview of your modeling task at any time.

Graphical user interfaces (GUIs) support the workflow.

SBPD features/capabilities include:

Project Representation --

Projects combine models, experiments, and measurements and allow you total control over your modeling projects.

Functions, such as manual parameter tuning, parameter estimation, model reduction, identifiability analysis, etc. can directly be applied to such projects.

High Performance Simulation --

For parameter estimation purposes the simulation speed is of crucial importance. Therefore, the SBPD package does Not rely on the standard integrators and compilers that are built-in to MATLAB (see Note 1).

Instead the simulations are performed by converting models to C-code and using the CVODES integrator package [CVODES - solves ODE (ordinary differential equation) systems and includes sensitivity analysis capabilities (forward and adjoint)] from SUNDIALS (SUite of Nonlinear and DIfferential/ALgebraic equation Solvers).

The 'benchmark ODE15s vs. SBPD' shows that due to that, the simulation performance increases by a factor somewhere between 30 and 150.

Manual Parameter Tuning --

The manual parameter tuning function allows you to change 'parameter values' and displays the results of the insilico experiments that are defined in the project in real-time.

This is a very valuable function for getting an insight into the effect of different parameters and a good way of giving a model its final accepted parameter settings.

Parameter Estimation --

Parameter estimation can be applied directly to a project. Any 'optimization method' that is available in MATLAB can be used.

However, to be independent of the MATLAB Optimization Toolbox (an additional product) several local and global optimization methods are available in the SBTOOLBOX2.

The parameter estimation functionality in SBPD automatically takes care of multiple experiments and multiple datasets in your projects.

Identifiability Analysis --

Prior to performing parameter estimation it is a good idea to assess the identifiability of the models parameters. Otherwise the estimation might return unreliable results.

Identifiability of parameters depends on the structure of the model, but also on the experiments that have been performed and the components that have been measured.

The SBPD package contains functionality to directly apply 'identifiability analysis' to projects.

Model Reduction --

Models of biochemical systems are usually highly over-parameterized with regard to the available measurement data. This renders the parameter estimation task difficult due to indentifiability issues.

One possibility is to reduce a models complexity.

The SBPD package contains ‘model reduction’functionality that can directly be applied to a chosen model in a project.

Summary of Main SBPD Features --

Additional Features --

Additionally, the SBPD package contains many auxiliary functions that are useful for facilitating the access to projects or data elements, writing your own scripts, and last but Not least to make it independent of other commercial MATLAB toolboxes and third party packages.

However, for just a few functions the presence of the MATLAB Symbolic Math Toolbox (an additional product) is required.

Extensive Documentation --

Tutorials - Collection of comprehensive tutorials for SBTOOLBOX2 and the SBPD extension package.

User's Reference - Complete extensive user's reference guide. All functions of SBPD are explained in detail and by examples.

Benchmark - Benchmark between SBPD simulation and standard MATLAB simulation using ODE15s.

Note 1: MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and FORTRAN.

System Requirements

Systems Biology Toolbox 2 for MATLAB - Requirements


Manufacturer Web Site SBPD extension package

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G6G Abstract Number 20360

G6G Manufacturer Number 104009