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

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.

[1]  Jens Timmer,et al.  Dynamical modeling and multi-experiment fitting with PottersWheel , 2008, Bioinform..

[2]  Andreas Rauh,et al.  Thermal behavior of high-temperature fuel cells: reliable parameter identification and interval-based sliding mode control , 2013, Soft Comput..

[3]  Baojun Song,et al.  Dynamics of starvation in humans , 2006, Journal of mathematical biology.

[4]  Melanie I. Stefan,et al.  BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models , 2010, BMC Systems Biology.

[5]  Guangquan Li,et al.  Parameter Identifiability and Redundancy: Theoretical Considerations , 2008, PloS one.

[6]  Zhike Zi,et al.  SBML-PET: a Systems Biology Markup Language-based parameter estimation tool , 2006, Bioinform..

[7]  Mudita Singhal,et al.  COPASI - a COmplex PAthway SImulator , 2006, Bioinform..

[8]  J. Tyson Modeling the cell division cycle: cdc2 and cyclin interactions. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Nicholas Bruchovsky,et al.  Final results of the Canadian prospective phase II trial of intermittent androgen suppression for men in biochemical recurrence after radiotherapy for locally advanced prostate cancer , 2006, Cancer.

[10]  Nicola Paoletti,et al.  Precise Parameter Synthesis for Stochastic Biochemical Systems , 2014, CMSB.

[11]  Mats Jirstrand,et al.  Systems biology Systems Biology Toolbox for MATLAB : a computational platform for research in systems biology , 2006 .

[12]  Lubos Brim,et al.  On Parameter Synthesis by Parallel Model Checking , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[13]  Thao Dang,et al.  Parameter synthesis for polynomial biological models , 2014, HSCC.

[14]  Edmund M. Clarke,et al.  Towards Personalized Cancer Therapy Using Delta-Reachability Analysis , 2014, ArXiv.

[15]  Calin Belta,et al.  Robustness analysis and tuning of synthetic gene networks , 2007, Bioinform..

[16]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[17]  Gilles Clermont,et al.  Parameter Synthesis in Nonlinear Dynamical Systems: Application to Systems Biology , 2009, RECOMB.

[18]  Sumit Kumar Jha,et al.  Synthesis and infeasibility analysis for stochastic models of biochemical systems using statistical model checking and abstraction refinement , 2011, Theor. Comput. Sci..

[19]  Edmund M. Clarke,et al.  Towards personalized prostate cancer therapy using delta-reachability analysis , 2014, HSCC.

[20]  Gouhei Tanaka,et al.  A Mathematical Model of Intermittent Androgen Suppression for Prostate Cancer , 2008, J. Nonlinear Sci..

[21]  Hiroaki Kitano,et al.  Foundations of systems biology , 2001 .

[22]  Alberto Griggio,et al.  Parameter synthesis with IC3 , 2013, 2013 Formal Methods in Computer-Aided Design.

[23]  Edmund M. Clarke,et al.  dReal: An SMT Solver for Nonlinear Theories over the Reals , 2013, CADE.

[24]  Adam Arkin,et al.  Setting the standard in synthetic biology , 2008, Nature Biotechnology.

[25]  A. Girard,et al.  Recent Progress in Continuoushybrid Reachability Analysis , 2006 .

[26]  Edmund M. Clarke,et al.  Delta-Decidability over the Reals , 2012, 2012 27th Annual IEEE Symposium on Logic in Computer Science.

[27]  Oded Maler,et al.  Recent progress in continuous and hybrid reachability analysis , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[28]  Nacim Meslem,et al.  Guaranteed Parameter Set Estimation for Monotone Dynamical Systems Using Hybrid Automata , 2010, Reliab. Comput..

[29]  Eva Balsa-Canto,et al.  AMIGO, a toolbox for advanced model identification in systems biology using global optimization , 2011, Bioinform..

[30]  Joseph A. Smith,et al.  Final results of the Canadian prospective phase II trial of intermittent androgen suppression for men in biochemical recurrence after radiotherapy for locally advanced prostate cancer: Clinical parameters , 2007 .

[31]  Calin Belta,et al.  Parameter Synthesis for Piecewise Affine Systems from Temporal Logic Specifications , 2008, HSCC.