title: Automated parameter estimation for biological models using Bayesian statistical model checking.
abstract: BACKGROUND
  Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem.
  
  
  RESULTS
  Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model.
  
  
  CONCLUSIONS
  We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.
authors.forename: Faraz
authors.initials: F
authors.lastname: Hussain
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Langmead
authors.forename: Qi
authors.initials: Q
authors.lastname: Mi
authors.forename: Joyeeta
authors.initials: J
authors.lastname: Dutta-Moscato
authors.forename: Yoram
authors.initials: Y
authors.lastname: Vodovotz
authors.forename: Sumit K
authors.initials: SK
authors.lastname: Jha
mesh_terms: D000208:Acute Disease; D000465:Algorithms; D001331:Automation; D001499:Bayes Theorem; D003198:Computer Simulation; D006801:Humans; D007249:Inflammation / Q000473:pathology; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D011336:Probability; D015203:Reproducibility of Results; D013269:Stochastic Processes; D049490:Systems Biology