GRENDEL

GRENDEL (Gene Regulatory Network Decoding Evaluations tooL), generates random gene regulatory networks according to user defined constraints on the network topology and kinetics. It then simulates the state of each regulatory network under various user defined conditions (the experimental design) and produces simulated gene expression data.

Releases

Version 0.2

Second release for the GRENDEL benchmark tool. Improvements include: support for gcc4, improved build process and error handling, and the addition of model compilation scripts to easily render a table of gene expression data from a model path.

Version 0.1

Initial release of GRENDEL: In this release support is provided for generating network topologies according to scale free (powerlaw) out-degree distributions and exponential in-degree distributions, Erdos-Renyi topologies (uniform degree distribution) and imported topologies. Kinetic regulatory functions provided in this release are: Hill Kinetics and Michaelis-Menten with combinatoric interactions between regulators. Experimental design types supported: genetically diverse population samples, knockouts, overexpression and time course with external stimuli perturbations