Programming Research Group Research Report RR-08-07

Christopher Fogelberg Vasile Palade

May 2008, 14pp.

Abstract

Inference of complete genetic regulatory networks is a central problem in modern bioinformatics. However, because good biological data is still relatively rare, it is hard to evaluate new machine learning techniques for network inference. In this report we describe GreenSim, a modular, customisable and extensible genetic regulatory network simulator. It accurately models motifs, non-linear regulatory functions and can generate networks ranging in size from N = 100 to N = 104 genes. Code is available online and from the authors.