@inproceedings{0682a83c4e2445e4b9827c0c7b444a63,
title = "Modeling of stochastic biological processes with non-polynomial propensities using non-central conditional moment equation",
abstract = "Biological processes exhibiting stochastic fluctuations are mainly modeled using the Chemical Master Equation (CME). As a direct simulation of the CME is often computationally intractable, we recently introduced the Method of Conditional Moments (MCM). The MCM is a hybrid approach to approximate the statistics of the CME solution. In this work, we provide a more comprehensive formulation of the MCM by using non-central conditional moments instead of central conditional moments. The modified formulation allows for additional insight into the model structure and for extensions to higher-order reactions and non-polynomial propensity functions. The properties of the non-central MCM are analyzed using a model for the regulation of pili formation on the surface of bacteria, which possesses rational propensity functions.",
keywords = "Chemical master equation, Moment equations, Stochastic modeling",
author = "Atefeh Kazeroonian and Theis, {Fabian J.} and Jan Hasenauer",
note = "Publisher Copyright: {\textcopyright} IFAC.; 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 ; Conference date: 24-08-2014 Through 29-08-2014",
year = "2014",
doi = "10.3182/20140824-6-za-1003.02298",
language = "English",
series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",
publisher = "IFAC Secretariat",
pages = "1729--1735",
editor = "Edward Boje and Xiaohua Xia",
booktitle = "19th IFAC World Congress IFAC 2014, Proceedings",
}