Efficient stochastic simulation of systems with multiple time scales via statistical abstraction

Luca Bortolussi, Dimitrios Milios, Guido Sanguinetti

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Stiffness in chemical reaction systems is a frequently encountered computational problem, arising when different reactions in the system take place at different time-scales. Computational savings can be obtained under time-scale separation. Assuming that the system can be partitioned into slow- and fast- equilibrating subsystems, it is then possible to efficiently simulate the slow subsystem only, provided that the corresponding kinetic laws have been modified so that they reflect their dependency on the fast system. We show that the rate expectation with respect to the fast subsystem's steady-state is a continuous function of the state of the slow system. We exploit this result to construct an analytic representation of the modified rate functions via statistical modelling, which can be used to simulate the slow system in isolation. The computational savings of our approach are demonstrated in a number of non-trivial examples of stiff systems.
Original languageEnglish
Title of host publicationComputational Methods in Systems Biology
Subtitle of host publication13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings
PublisherSpringer International Publishing
Number of pages12
ISBN (Electronic)978-3-319-23401-4
ISBN (Print)978-3-319-23400-7
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
ISSN (Print)0302-9743


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