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arXiv · 1704.07722

A Convex Approach to Steady State Moment Analysis for Stochastic Chemical Reactions

Yuta Sakurai·Yutaka Hori
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Abstract

Model-based prediction of stochastic noise in biomolecular reactions often resorts to approximation with unknown precision. As a result, unexpected stochastic fluctuation causes a headache for the designers of biomolecular circuits. This paper proposes a convex optimization approach to quantifying the steady state moments of molecular copy counts with theoretical rigor. We show that the stochastic moments lie in a convex semi-algebraic set specified by linear matrix inequalities. Thus, the upper and the lower bounds of some moments can be computed by a semidefinite program. Using a protein dimerization process as an example, we demonstrate that the proposed method can precisely predict the mean and the variance of the copy number of the monomer protein.

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BibTeXRIS

Yuta Sakurai, Yutaka Hori. 2017-04-25. A Convex Approach to Steady State Moment Analysis for Stochastic Chemical Reactions. https://doi.org/10.1109/cdc.2017.8263820

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