Stochastic Simulation of Biomolecular Networks in Dynamic Environments.
Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sam...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2016-06-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004923&type=printable |
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| author | Margaritis Voliotis Philipp Thomas Ramon Grima Clive G Bowsher |
| author_facet | Margaritis Voliotis Philipp Thomas Ramon Grima Clive G Bowsher |
| author_sort | Margaritis Voliotis |
| collection | DOAJ |
| description | Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. |
| format | Article |
| id | doaj-art-8fb5f3305e10482f88060b8136d4e78f |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2016-06-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-8fb5f3305e10482f88060b8136d4e78f2025-08-20T02:03:16ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-06-01126e100492310.1371/journal.pcbi.1004923Stochastic Simulation of Biomolecular Networks in Dynamic Environments.Margaritis VoliotisPhilipp ThomasRamon GrimaClive G BowsherSimulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004923&type=printable |
| spellingShingle | Margaritis Voliotis Philipp Thomas Ramon Grima Clive G Bowsher Stochastic Simulation of Biomolecular Networks in Dynamic Environments. PLoS Computational Biology |
| title | Stochastic Simulation of Biomolecular Networks in Dynamic Environments. |
| title_full | Stochastic Simulation of Biomolecular Networks in Dynamic Environments. |
| title_fullStr | Stochastic Simulation of Biomolecular Networks in Dynamic Environments. |
| title_full_unstemmed | Stochastic Simulation of Biomolecular Networks in Dynamic Environments. |
| title_short | Stochastic Simulation of Biomolecular Networks in Dynamic Environments. |
| title_sort | stochastic simulation of biomolecular networks in dynamic environments |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004923&type=printable |
| work_keys_str_mv | AT margaritisvoliotis stochasticsimulationofbiomolecularnetworksindynamicenvironments AT philippthomas stochasticsimulationofbiomolecularnetworksindynamicenvironments AT ramongrima stochasticsimulationofbiomolecularnetworksindynamicenvironments AT clivegbowsher stochasticsimulationofbiomolecularnetworksindynamicenvironments |