## ByoDyn

** Category** Cross-Omics>Pathway Analysis/Tools

** Abstract** ByoDyn is a 'computational framework' that can be used to
study the dynamical behavior of gene regulatory networks (GRNs) and
for parameter estimation in uni- and multicellular models.

Recent 'systems biology' approaches have given a second life to classical biochemical kinetics methods. It is becoming a routine task to build models of increasing complexity on a given gene regulatory, signal transduction or metabolic network or pathway of interest.

One of the main problems in building such models is the determination of the parameters underlying each modeled equation or process.

ByoDyn has been designed to provide an easily extendable 'computational framework' to deal with the estimation of parameters in highly uncharacterized models.

There are five (5) main features/capabilities of ByoDyn:

1) Run quantitative simulations of unicellular or multicellular biochemical networks both deterministically and stochastically.

2) Perform analysis of the sensitivity of the system with respect to the parameters of the model.

3) Estimate the numerical values of the biochemical parameters that match a given set of experimental data along 'time' for any of the system's nodes.

4) Use the Fisher information matrix to help in designing optimal experiments for the calibration problem.

5) Determine the global shape of the parameter space thanks to Monte Carlo sampling coupled with cluster analysis and Principal Component Analysis (PCA).

ByoDyn Simulations --

ByoDyn uses Systems Biology Markup Language (SBML) format files to run unicellular systems or a homemade format for multicellular models.

A parser based on libSBML has been developed to build the system of (nonlinear) ordinary differential equations (ODEs).

*Note: LibSBML is an open-source programming library to help you
read, write, manipulate, translate, and validate SBML files and data
streams.*

It is Not an application itself (though it does come with example programs), but rather a library you can embed in your own applications.

ByoDyn uses several routines from SciPy (The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization) to solve the above problem.

Also, the package LSODA (Livermore Solver for Ordinary Differential equations), is called because of its ability to switch automatically between both stiff and non-stiff integrators when necessary.

As a secondary possibility ByoDyn can also make external calls to:

a) Octave (Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB);

b) OpenModelica (OpenModelica is an object-oriented, declarative, multi-domain 'modeling language' for component-oriented modeling of complex systems);

and c) XPPAUT (XPPAUT is a tool for solving differential equations, difference equations, delay equations, functional equations, boundary value problems, and stochastic equations);

which is an advanced approach in order to solve other system equations such as differential algebraic equations (DAEs), events or delays via delay differential equations (DDEs).

ByoDyn uses several functions to create PostScript or Portable Network Graphics (PNG) plots such as trajectories of the 'node concentration' along time for unicellular systems and cell matrices where the steady state node concentration is shown by color intensity.

Sensitivity, identifiability, optimal experimental design and many other functions also render to appropriate graphs.

ByoDyn Sensitivity analysis --

The sensitivity analysis of the system along time with respect to a specific parameter is also performed.

This step allows you to discriminate the parameters that are less affecting the dynamics of the system and that therefore might be excluded from the optimization routines.

Global sensitivity can be explored thanks to the Monte Carlo sampling and principal component analysis (PCA) of the resulting cluster of solutions.

ByoDyn Parameter estimation --

If temporal quantitative data about the expression of the nodes is known along time, ByoDyn uses state of the art optimization algorithms to obtain the numerical values of the biochemical parameters that reproduce the given experimental behavior.

The manufacturer has implemented different global and local optimization methods to obtain the best set of parameters in each particular case.

ByoDyn Optimal experimental design --

Analysis of the covariance matrix for the change in the fitness function with respect to the parameters has lead to the implementation of optimal experimental design approaches.

Fisher information matrix analyses are executed to assess which point results are more informative for the ‘model calibration’ problem.

*System Requirements*

ByoDyn is an object oriented (OO), Python based, program that makes use of several 'open source' libraries freely available for non- commercial use:

The PORT library from Netlib for Newtonian optimizations; the SciPy package version 0.6.0 for scientific libraries in Python, including the ODE solvers; and the libSBML (Gnu LGPL) library version 3.2.0 for handling SBML files.

The program has been tested on Linux Fedora Core 2 and 4 and on Mac OS X platforms and its migration to any other platform is straightforward.

*Manufacturer*

- Computational Biochemistry and Biophysics Laboratory (CBBL)
- Research Unit on Biomedical Informatics (GRIB)
- Barcelona Biomedical Research Park (PRBB)
- C/Doctor Aiguader, 88
- E-08003 Barcelona, Spain
- Tel: 34-93-3160504
- Fax: 34-93-3160550

** Manufacturer Web Site**
ByoDyn

** Price** Contact manufacturer.

** G6G Abstract Number** 20458

** G6G Manufacturer Number** 104086