What do molecules do when we are not looking? State sequence analysis for stochastic chemical systems
Author(s) -
Pavel Levin,
Jérémie Lefebvre,
Theodore J. Perkins
Publication year - 2012
Publication title -
journal of the royal society interface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 139
eISSN - 1742-5689
pISSN - 1742-5662
DOI - 10.1098/rsif.2012.0633
Subject(s) - sequence (biology) , stochastic process , trajectory , computer science , dynamical systems theory , rare events , discretization , stochastic modelling , statistical physics , scale (ratio) , state (computer science) , theoretical computer science , biological system , algorithm , mathematics , physics , biology , genetics , statistics , mathematical analysis , quantum mechanics , astronomy
Many biomolecular systems depend on orderly sequences of chemical transformations or reactions. Yet, the dynamics of single molecules or small-copy-number molecular systems are significantly stochastic. Here, we propose state sequence analysis--a new approach for predicting or visualizing the behaviour of stochastic molecular systems by computing maximum probability state sequences, based on initial conditions or boundary conditions. We demonstrate this approach by analysing the acquisition of drug-resistance mutations in the human immunodeficiency virus genome, which depends on rare events occurring on the time scale of years, and the stochastic opening and closing behaviour of a single sodium ion channel, which occurs on the time scale of milliseconds. In both cases, we find that our approach yields novel insights into the stochastic dynamical behaviour of these systems, including insights that are not correctly reproduced in standard time-discretization approaches to trajectory analysis.
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