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BioPSy: An SMT-based Tool for Guaranteed Parameter Set Synthesis of Biological Models

  • Curtis Madsen
  • Fedor Shmarov
  • Paolo Zuliani
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9308)

Abstract

The parameter set synthesis problem consists of identifying sets of parameter values for which a given system model satisfies a desired behaviour. This paper presents BioPSy, a tool that performs guaranteed parameter set synthesis for ordinary differential equation (ODE) biological models expressed in the Systems Biology Markup Language (SBML) given a desired behaviour expressed by time-series data. Three key features of BioPSy are: (1) BioPSy computes parameter intervals, not just single values; (2) for the identified intervals the model is formally guaranteed to satisfy the desired behaviour; and (3) BioPSy can handle virtually any Lipschitz-continuous ODEs, including nonlinear ones. BioPSy is able to achieve guaranteed synthesis by utilising Satisfiability Modulo Theory (SMT) solvers to determine acceptable parameter intervals. We have successfully applied our tool to several biological models including a prostate cancer therapy model, a human starvation model, and a cell cycle model.

Keywords

Biological Model Synthesis Problem Parameter Synthesis Satisfiability Modulo Theory Prostate Cancer Treatment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

C. M. has been supported by the Engineering and Physical Sciences Research Council (UK) grant EP/K039083/1; F. S. has been supported by award N00014-13-1-0090 of the US Office of Naval Research.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computing ScienceNewcastle UniversityNewcastle upon TyneUK

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