Lookup NU author(s): Daven Sanassy,
Dr Pawel Widera,
Professor Natalio Krasnogor
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Stochastic simulation algorithms (SSAs) are used to trace realistic trajectories of biochemical systems at low species concentrations. As the complexity of modeled biosystems increases, it is important to select the best performing SSA. Numerous improvements to SSAs have been introduced but they each only tend to apply to a certain class of models. This makes it difficult for a systems or synthetic biologist to decide which algorithm to employ when confronted with a new model that requires simulation. In this paper, we demonstrate that it is possible to determine which algorithm is best suited to simulate a particular model and that this can be predicted a priori to algorithm execution. We present a Web based tool ssapredict that allows scientists to upload a biochemical model and obtain a prediction of the best performing SSA. Furthermore, ssapredict gives the user the option to download our high performance simulator ngss preconfigured to perform the simulation of the queried biochemical model with the predicted fastest algorithm as the simulation engine.
Author(s): Sanassy D, Widera P, Krasnogor N
Publication type: Article
Publication status: Published
Journal: ACS Synthetic Biology
Print publication date: 01/01/2015
Online publication date: 22/08/2014
Acceptance date: 07/03/2014
ISSN (electronic): 2161-5063
Publisher: American Chemical Society
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