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Fisher and Henzinger [10] called the approach executable biology.
The SMS is an example of a class of simulation models referred to as executable biology [ 31, 32].
Recently, the term executable biology has been proposed for models that consist of an algorithm which mimics the behavior of a studied biological system [ 12].
The envisioned products are examples of executable biology [ 6- 8], which are useful for systematically exploring hypotheses about referent mechanisms through virtual experimentation.
Key to this transition from descriptive to executable biology is the development of mathematical models that represent the dynamic properties of biological processes and their corresponding computational models that can be executed in silico.
Executable Biology (Fisher and Henzinger, 2007; Fisher and Piterman, 2010) is an evolving paradigm that focuses on the design of executable computer algorithms that mimic biological phenomena through the use of formal methods from engineering and computer science.
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We present a new method for random testing of binary executables inspired by biology.
The computational model is executed using a novel multi-compartment Monte Carlo stochastic algorithm using the mcss simulator, which is part of the Infobiotics workbench, a freely available software suite for designing, simulating and analysing multiscale executable systems and synthetic biology models [ 29].
It is important to clarify that iTools does not include a tool-integration environment, nor does it include the binary executable components of the corresponding computational biology resources.
Conversely in synthetic biology models are employed as executable prototypes/designs for engineering useful synthetic biological systems.
Afterwards, the execution phase processes each executable statement sequentially.
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