SELANSI: a toolbox for simulation of stochastic gene regulatory networks

Abstract

Motivation Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an… (More)
DOI: 10.1093/bioinformatics/btx645

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