Trace Simplifications Preserving Temporal Logic Formulae with Case Study in a Coupled Model of the Cell Cycle and the Circadian Clock

Calibrating dynamical models on experimental data time series is a central task in computational systems biology. When numerical values for model parameters can be found to fit the data, the model can be used to make predictions, whereas the absence of any good fit may suggest to revisit the structure of the model and gain new insights in the biology of the system. Temporal logic provides a formal framework to deal with imprecise data and specify a wide variety of dynamical behaviors. It can be used to extract information from numerical traces coming from either experimental data or model simulations, and to specify the expected behaviors for model calibration. The computation time of the different methods depends on the number of points in the trace so the question of trace simplification is important to improve their performance. In this paper we study this problem and provide a series of trace simplifications which are correct to perform for some common temporal logic formulae. We give some general soundness theorems, and apply this approach to period and phase constraints on the circadian clock and the cell cycle. In this application, temporal logic patterns are used to compute the relevant characteristics of the experimental traces, and to measure the adequacy of the model to its specification on simulation traces. Speed-ups by several orders of magnitude are obtained by trace simplification even when produced by smart numerical integration methods.

[1]  Oded Maler,et al.  Robust Satisfaction of Temporal Logic over Real-Valued Signals , 2010, FORMATS.

[2]  J. Weiss,et al.  Dynamics of the cell cycle: checkpoints, sizers, and timers. , 2003, Biophysical journal.

[3]  Thomas Ferrère,et al.  Efficient Robust Monitoring for STL , 2013, CAV.

[4]  Patrick Cousot,et al.  Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints , 1977, POPL.

[5]  François Fages,et al.  On temporal logic constraint solving for analyzing numerical data time series , 2008, Theor. Comput. Sci..

[6]  Felix Naef,et al.  Circadian Gene Expression in Individual Fibroblasts Cell-Autonomous and Self-Sustained Oscillators Pass Time to Daughter Cells , 2004, Cell.

[7]  Jirí Srba,et al.  Comparing the Expressiveness of Timed Automata and Timed Extensions of Petri Nets , 2008, FORMATS.

[8]  S. Yamaguchi,et al.  Control Mechanism of the Circadian Clock for Timing of Cell Division in Vivo , 2003, Science.

[9]  Radu Mateescu,et al.  Validation of qualitative models of genetic regulatory networks by model checking: analysis of the nutritional stress response in Escherichia coli , 2005, ISMB.

[10]  François Fages,et al.  Symbolic Model Checking of Biochemical Networks , 2003, CMSB.

[11]  H. D. Jong,et al.  Qualitative simulation of genetic regulatory networks using piecewise-linear models , 2004, Bulletin of mathematical biology.

[12]  A. Goldbeter,et al.  Toward a detailed computational model for the mammalian circadian clock , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[13]  François Fages,et al.  A general computational method for robustness analysis with applications to synthetic gene networks , 2009, Bioinform..

[14]  Gregor Gößler,et al.  Efficient parameter search for qualitative models of regulatory networks using symbolic model checking , 2010, Bioinform..

[15]  Philippe Schnoebelen,et al.  Model Checking a Path , 2003, CONCUR.

[16]  Adrien Richard,et al.  Application of formal methods to biological regulatory networks: extending Thomas' asynchronous logical approach with temporal logic. , 2004, Journal of theoretical biology.

[17]  Grigore Rosu,et al.  Rewriting-Based Techniques for Runtime Verification , 2005, Automated Software Engineering.

[18]  Alberto Policriti,et al.  Model building and model checking for biochemical processes , 2007, Cell Biochemistry and Biophysics.

[19]  François Fages,et al.  Continuous valuations of temporal logic specifications with applications to parameter optimization and robustness measures , 2011, Theor. Comput. Sci..

[20]  Cnrs Fre,et al.  Model Checking a Path (Preliminary Report) , 2003 .

[21]  Ian Stark,et al.  The Continuous pi-Calculus: A Process Algebra for Biochemical Modelling , 2008, CMSB.

[22]  François Fages,et al.  New Results - Temporal Logic Modeling of Dynamical Behaviors: First-Order Patterns and Solvers , 2014 .

[23]  Edmund M. Clarke,et al.  Model Checking , 1999, Handbook of Automated Reasoning.

[24]  François Fages,et al.  Competing G protein-coupled receptor kinases balance G protein and β-arrestin signaling , 2012, Molecular systems biology.

[25]  José Meseguer,et al.  Pathway Logic: Symbolic Analysis of Biological Signaling , 2001, Pacific Symposium on Biocomputing.