Abstract
Background: Discrete simulations of genetic regulatory networks have been used
to study subsystems of yeast successfully. However, implementations of the two
models underlying these simulations do not support a graphic interface, are not
freely available, and require computations necessary to analyze their results to be
done manually. Furthermore, differences between these two models suggest that
an enriched model, encompassing both existing models, is needed.
Results: We developed a software tool, called GRegNetSim, that allows the
end-user (a biologist) to describe genetic regulatory networks graphically. The
input is graphic (as an input to Cytoscape, an open-source platform for the
representation and analysis of biological networks). The user can specify various
transition functions at different nodes of the network, supporting, for example,
threshold and gradient effects, and then apply the network to a variety of inputs.
GRegNetSim displays the relationship between the inputs and the mode of
behavior of the network in a graphic form that is easy to interpret. Furthermore,
it can automatically extract statistical data necessary to analyze the simulations.
Conclusions: The discrete simulations performed by GRegNetSim can be used
to elucidate and predict the behavior, structure and properties of genetic
regulatory networks in a unified manner. GRegNetSim is implemented as a
Cytoscape App. Installation files, examples and source code, along with a detailed
user guide, are freely available at https://sites.google.com/site/gregnetsim/
to study subsystems of yeast successfully. However, implementations of the two
models underlying these simulations do not support a graphic interface, are not
freely available, and require computations necessary to analyze their results to be
done manually. Furthermore, differences between these two models suggest that
an enriched model, encompassing both existing models, is needed.
Results: We developed a software tool, called GRegNetSim, that allows the
end-user (a biologist) to describe genetic regulatory networks graphically. The
input is graphic (as an input to Cytoscape, an open-source platform for the
representation and analysis of biological networks). The user can specify various
transition functions at different nodes of the network, supporting, for example,
threshold and gradient effects, and then apply the network to a variety of inputs.
GRegNetSim displays the relationship between the inputs and the mode of
behavior of the network in a graphic form that is easy to interpret. Furthermore,
it can automatically extract statistical data necessary to analyze the simulations.
Conclusions: The discrete simulations performed by GRegNetSim can be used
to elucidate and predict the behavior, structure and properties of genetic
regulatory networks in a unified manner. GRegNetSim is implemented as a
Cytoscape App. Installation files, examples and source code, along with a detailed
user guide, are freely available at https://sites.google.com/site/gregnetsim/
| Original language | English |
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| Place of Publication | Haifa |
| Publisher | Technion - Israel Institute of Technology, Faculty of Computer Science |
| Number of pages | 8 |
| State | Published - 2017 |
Publication series
| Name | Technical Report CS-2017-03 - 2017 |
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