Parameter discovery for stochastic biological models against temporal behavioral specifications using an SPRT based Metric for simulated annealing

Stochastic models are often used to study the behavior of biochemical systems and biomedical devices. While the structure of such models is often readily available from first principles, several quantitative features of the model are not easily determined. These quantitative features are often incorporated into the model as parameters. The algorithmic discovery of parameter values from experimentally observed facts (including extreme-scale data) remains a challenge for the computational systems biology community. In this paper, we present a new parameter discovery algorithm based on Wald's sequential probability ratio test (SPRT). Our algorithm uses a combination of simulated annealing and sequential hypothesis testing to reduce the number of samples required for parameter discovery of stochastic models. We use probabilistic bounded linear temporal logic (PBLTL) to express the desired behavioral specification of a model. We also present theoretical results on the correctness of our algorithm, and demonstrate the effectiveness of our algorithm by studying a detailed model of glucose and insulin metabolism.

• Publication year

  2012

• Venue

  International Conference on Computational Advances in Bio and Medical Sciences

• Publication date

  2012-02-01

• Fields of study

  Biology, Computer Science

• Identifiers
  DOI 10.1109/ICCABS.2012.6182640
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Synthesis of insulin pump controllers from safety specifications using Bayesian model validation

  2012cited by this paper
• Exploring behaviors of SDE models of biological systems using change of measures

  2011cited by this paper
• When to stop verification?: Statistical trade-off between expected loss and simulation cost

  2011cited by this paper
• Parallel Algorithms for Bayesian Networks Structure Learning with Applications to Systems Biology

  2011cited by this paper
• d-IRA: A Distributed Reachability Algorithm for Analysis of Linear Hybrid Automata

  2008cited by this paper
• A Parallel Algorithm for Learning Bayesian Networks

  2007cited by this paper
• Temporal Logic of Programs

  1987influential reference
• Stochastics Models, Estimation, and Control: Introduction

  1979cited by this paper
• Bioinformatics Applications Note Systems Biology Mapreduce Implementation of a Hybrid Spectral Library-database Search Method for Large-scale Peptide Identification

  year unknowncited by this paper

• Techniques for automated parameter estimation in computational models of probabilistic systems

  2016influential citation
• Automated parameter estimation for biological models using Bayesian statistical model checking

  2015cites this paper
• Computing Biological Model Parameters by Parallel Statistical Model Checking

  2015cites this paper
• EpiSpec: A formal specification language for parameterized agent-based models against epidemiological ground truth

  2014cites this paper
• Parameter discovery for stochastic computational models in systems biology using Bayesian model checking

  2014cites this paper
• Patient-specific models from inter-patient biological models and clinical records

  2014cites this paper
• A computational metabolic model of the NG108-15 cell for high content drug screening with electrophysiological readout

  2012cites this paper