FERN - a Java framework for stochastic simulation and evaluation of reaction networks

Background: Stochastic simulation can be used to illustrate the
development of biological systems over time and the stochastic
nature of these processes. Currently available programs for
stochastic simulation, however, are limited in that they either a)
do not provide the most efficient simulation algorithms and are
difficult to extend, b) cannot be easily integrated into other
applications or c) do not allow to monitor and intervene during the
simulation process in an easy and intuitive way. Thus, in order to
use stochastic simulation in innovative high-level modeling and
analysis approaches more flexible tools are necessary. Results: In
this article, we present FERN (Framework for Evaluation of Reaction
Networks), a Java framework for the efficient simulation of
chemical reaction networks. FERN is subdivided into three layers
for network representation, simulation and visualization of the
simulation results each of which can be easily extended. It
provides efficient and accurate state-of-the-art stochastic
simulation algorithms for well-mixed chemical systems and a
powerful observer system, which makes it possible to track and
control the simulation progress on every level. To illustrate how
FERN can be easily integrated into other systems biology
applications, plugins to Cytoscape and CellDesigner are included.
These plugins make it possible to run simulations and to observe
the simulation progress in a reaction network in real-time from
within the Cytoscape or CellDesigner environment. Conclusion: FERN
addresses shortcomings of currently available stochastic simulation
programs in several ways. First, it provides a broad range of
efficient and accurate algorithms both for exact and approximate
stochastic simulation and a simple interface for extending to new
algorithms. FERN's implementations are considerably faster than the
C implementations of gillespie2 or the Java implementations of
ISBJava. Second, it can be used in a straightforward way both as a
stand-alone program and within new systems biology applications.
Finally, complex scenarios requiring intervention during the
simulation progress can be modelled easily with FERN.