@article{
 title = {Approximation of event probabilities in noisy cellular processes},
 type = {article},
 year = {2011},
 keywords = {[Chemical master equation, Gillespie simulation, I},
 volume = {412},
 id = {dc5819d4-b581-388f-b60c-f6be3f8d1ad4},
 created = {2017-01-02T09:34:04.000Z},
 file_attached = {false},
 profile_id = {bbb99b2d-2278-3254-820f-2de6d915ce63},
 last_modified = {2017-03-22T13:51:34.979Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Molecular noise, which arises from the randomness of the discrete events in the cell, significantly influences fundamental biological processes. Discrete-state continuous-time stochastic models (CTMC) can be used to describe such effects, but the calculation of the probabilities of certain events is computationally expensive. We present a comparison of two analysis approaches for CTMC. On one hand, we estimate the probabilities of interest using repeated Gillespie simulation and determine the statistical accuracy that we obtain. On the other hand, we apply a numerical reachability analysis that approximates the probability distributions of the system at several time instances. We use examples of cellular processes to demonstrate the superiority of the reachability analysis if accurate results are required. © 2011 Elsevier B.V. All rights reserved.},
 bibtype = {article},
 author = {Didier, F. and Henzinger, T.A. and Mateescu, M. and Wolf, V.},
 doi = {10.1016/j.tcs.2010.10.022},
 journal = {Theoretical Computer Science},
 number = {21}
}

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