Prof. Meirav Zehavi

Discrete simulations of genetic regulatory networks have been used to study subsystems of yeast successfully. Existing models underling these simulations are based on specific transition functions, which determine the node states in the network. However, implementations of existing models are not freely available and support only a textual user interface (TUI). Additionally, even if an implementation that supports a graphic user interface (GUI) were available, the computations necessary to analyze the simulations would still have to be done manually. Furthermore, the usage of different transition functions by existing models suggests that an enriched model is needed. We developed a software tool, called GRegNetSim, that allows the end-user (a biologist) to describe genetic regulatory networks graphically. The input is displayed visually via 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, thereby analyzing the network under a variety of modes dictated by these functions. 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 automatically extracts statistical data such as the percentage of simulations that reached a steady state or the percentage of simulations that terminated with a certain state. 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/.