A Look-Ahead Simulation Algorithm for DBN Models of Biochemical Pathways View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2016

AUTHORS

Sucheendra K. Palaniappan , Matthieu Pichené , Grégory Batt , Eric Fabre , Blaise Genest

ABSTRACT

Dynamic Bayesian Networks (DBNs) have been proposed [16] as an efficient abstraction formalism of biochemical models. They have been shown to approximate well the dynamics of biochemical models, while offering improved efficiency for their analysis [17, 18]. In this paper, we compare different representations and simulation schemes on these DBNs, testing their efficiency and accuracy as abstractions of biological pathways. When generating these DBNs, many configurations are never explored by the underlying dynamics of the biological systems. This can be used to obtain sparse representations to store and analyze DBNs in a compact way. On the other hand, when simulating these DBNs, singular configurations may be encountered, that is configurations from where no transition probability is defined. This makes simulation more complex. We initially evaluate two simple strategies for dealing with singularities: First, re-sampling simulations visiting singular configurations; second filling up uniformly these singular transition probabilities. We show that both these approaches are error prone. Next, we propose a new algorithm which samples only those configurations that avoid singularities by using a look-ahead strategy. Experiments show that this approach is the most accurate while having a reasonable run time. More... »

PAGES

3-19

References to SciGraph publications

  • 2005. Monte Carlo Model Checking in TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS
  • 2008. A Model Checking Approach to the Parameter Estimation of Biochemical Pathways in COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY
  • 2009. Sliding Window Abstraction for Infinite Markov Chains in COMPUTER AIDED VERIFICATION
  • 2002. PRISM: Probabilistic Symbolic Model Checker in COMPUTER PERFORMANCE EVALUATION: MODELLING TECHNIQUES AND TOOLS
  • 2007. On the Analysis of Numerical Data Time Series in Temporal Logic in COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY
  • 2009. Probabilistic Approximations of Signaling Pathway Dynamics in COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY
  • 2009. A Bayesian Approach to Model Checking Biological Systems in COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY
  • 2007. Rule-Based Modelling of Cellular Signalling in CONCUR 2007 – CONCURRENCY THEORY
  • 2006. Analysis of Signalling Pathways Using Continuous Time Markov Chains in TRANSACTIONS ON COMPUTATIONAL SYSTEMS BIOLOGY VI
  • Book

    TITLE

    Hybrid Systems Biology

    ISBN

    978-3-319-47150-1
    978-3-319-47151-8

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-47151-8_1

    DOI

    http://dx.doi.org/10.1007/978-3-319-47151-8_1

    DIMENSIONS

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