CRA toolbox: software package for conditional robustness analysis of cancer systems biology models in MATLAB

Background In cancer research, robustness of a complex biochemical network is one of the most relevant properties to investigate for the development of novel targeted therapies. In cancer systems biology, biological networks are typically modeled through Ordinary Differential Equation (ODE) models....

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Vydané v:BMC bioinformatics Ročník 20; číslo 1; s. 385 - 19
Hlavní autori: Bianconi, Fortunato, Antonini, Chiara, Tomassoni, Lorenzo, Valigi, Paolo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London BioMed Central 09.07.2019
BMC
Predmet:
Algorithms
Analysis and modelling of complex systems
Bioinformatics
Biomedical and Life Sciences
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Conditional robustness analysis
Life Sciences
MATLAB package
Microarrays
Ordinary differential equation models
Signaling networks
Software
Ordinary differential equation models
Conditional robustness analysis
MATLAB package
Signaling networks
ISSN:1471-2105, 1471-2105
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Shrnutí:Background In cancer research, robustness of a complex biochemical network is one of the most relevant properties to investigate for the development of novel targeted therapies. In cancer systems biology, biological networks are typically modeled through Ordinary Differential Equation (ODE) models. Hence, robustness analysis consists in quantifying how much the temporal behavior of a specific node is influenced by the perturbation of model parameters. The Conditional Robustness Algorithm (CRA) is a valuable methodology to perform robustness analysis on a selected output variable, representative of the proliferation activity of cancer disease. Results Here we introduce our new freely downloadable software, the CRA Toolbox. The CRA Toolbox is an Object-Oriented MATLAB package which implements the features of CRA for ODE models. It offers the users the ability to import a mathematical model in Systems Biology Markup Language (SBML), to perturb the model parameter space and to choose the reference node for the robustness analysis. The CRA Toolbox allows the users to visualize and save all the generated results through a user-friendly Graphical User Interface (GUI). The CRA Toolbox has a modular and flexible architecture since it is designed according to some engineering design patterns. This tool has been successfully applied in three nonlinear ODE models: the Prostate-specific Pten −/− mouse model, the Pulse Generator Network and the EGFR-IGF1R pathway. Conclusions The CRA Toolbox for MATLAB is an open-source tool implementing the CRA to perform conditional robustness analysis. With its unique set of functions, the CRA Toolbox is a remarkable software for the topological study of biological networks. The source and example code and the corresponding documentation are freely available at the web site: http://gitlab.ict4life.com/SysBiOThe/CRA-Matlab .
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-019-2933-z