Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation

Vincent Wagner, Benjamin Castellaz, Marco Oesting, View ORCID ProfileNicole Radde
doi: https://doi.org/10.1101/2021.12.01.470753
Vincent Wagner
1Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Benjamin Castellaz
1Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marco Oesting
2Stuttgart Center for Simulation Science, University of Stuttgart, Pfaffenwaldring 5a, 70569 Stuttgart, Germany
3Institute for Stochastics and Applications, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicole Radde
1Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
2Stuttgart Center for Simulation Science, University of Stuttgart, Pfaffenwaldring 5a, 70569 Stuttgart, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Nicole Radde
  • For correspondence: Nicole.Radde@ist.uni-stuttgart.de
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Motivation The Chemical Master Equation is the most comprehensive stochastic approach to describe the evolution of a (bio-)chemical reaction system. Its solution is a time-dependent probability distribution on all possible configurations of the system. As the number of possible configurations is typically very large, the Master Equation is often practically unsolvable. The Method of Moments reduces the system to the evolution of a few moments of this distribution, which are described by a system of ordinary differential equations. Those equations are not closed, since lower order moments generally depend on higher order moments. Various closure schemes have been suggested to solve this problem, with different advantages and limitations. Two major problems with these approaches are first that they are open loop systems, which can diverge from the true solution, and second, some of them are computationally expensive.

Results Here we introduce Quasi-Entropy Closure, a moment closure scheme for the Method of Moments which estimates higher order moments by reconstructing the distribution that minimizes the distance to a uniform distribution subject to lower order moment constraints. Quasi-Entropy closure is similar to Zero-Information closure, which maximizes the information entropy. Results show that both approaches outperform truncation schemes. Moreover, Quasi-Entropy Closure is computationally much faster than Zero-Information Closure. Finally, our scheme includes a plausibility check for the existence of a distribution satisfying a given set of moments on the feasible set of configurations. Results are evaluated on different benchmark problems.

Figure
  • Download figure
  • Open in new tab

Competing Interest Statement

The authors have declared no competing interest.

  • Abbreviations

    (CME)
    Chemical Master Equation
    (MoM)
    Method of Moments
    (ODE)
    Ordinary Differential Equation
    (QEC)
    Quasi-Entropy Closure
    (SSA)
    Stochastic Simulation Algorithm
    (TC)
    Truncation Closure
    (ZIC)
    Zero-Information Closure
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
    Back to top
    PreviousNext
    Posted December 02, 2021.
    Download PDF
    Email

    Thank you for your interest in spreading the word about bioRxiv.

    NOTE: Your email address is requested solely to identify you as the sender of this article.

    Enter multiple addresses on separate lines or separate them with commas.
    Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation
    (Your Name) has forwarded a page to you from bioRxiv
    (Your Name) thought you would like to see this page from the bioRxiv website.
    CAPTCHA
    This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
    Share
    Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation
    Vincent Wagner, Benjamin Castellaz, Marco Oesting, Nicole Radde
    bioRxiv 2021.12.01.470753; doi: https://doi.org/10.1101/2021.12.01.470753
    Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
    Citation Tools
    Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation
    Vincent Wagner, Benjamin Castellaz, Marco Oesting, Nicole Radde
    bioRxiv 2021.12.01.470753; doi: https://doi.org/10.1101/2021.12.01.470753

    Citation Manager Formats

    • BibTeX
    • Bookends
    • EasyBib
    • EndNote (tagged)
    • EndNote 8 (xml)
    • Medlars
    • Mendeley
    • Papers
    • RefWorks Tagged
    • Ref Manager
    • RIS
    • Zotero
    • Tweet Widget
    • Facebook Like
    • Google Plus One

    Subject Area

    • Systems Biology
    Subject Areas
    All Articles
    • Animal Behavior and Cognition (4863)
    • Biochemistry (10813)
    • Bioengineering (8058)
    • Bioinformatics (27355)
    • Biophysics (14008)
    • Cancer Biology (11149)
    • Cell Biology (16091)
    • Clinical Trials (138)
    • Developmental Biology (8803)
    • Ecology (13313)
    • Epidemiology (2067)
    • Evolutionary Biology (17379)
    • Genetics (11699)
    • Genomics (15943)
    • Immunology (11046)
    • Microbiology (26133)
    • Molecular Biology (10669)
    • Neuroscience (56677)
    • Paleontology (420)
    • Pathology (1737)
    • Pharmacology and Toxicology (3011)
    • Physiology (4560)
    • Plant Biology (9653)
    • Scientific Communication and Education (1617)
    • Synthetic Biology (2696)
    • Systems Biology (6987)
    • Zoology (1511)