Parameter inference for asynchronous logical networks using discrete time series

This paper is concerned with the dynamics of asynchronous logical models of regulatory networks as introduced by R. Thomas. Available knowledge about the dynamics of a regulatory network is often limited to a sequence of snapshots in the form of a discrete time series. Using CTL formulas together with the concept of partially monotone paths, a methodology is elaborated to investigate the compatibility of a given time series and a Thomas model. The approach can be used to revise the model, but also to evaluate the given data. Additionally, suggestions are made to analyze a model pool for common properties regarding component behavior and interaction types, aiming at results exploitable for experimental design.

[1]  Marco Pistore,et al.  NuSMV 2: An OpenSource Tool for Symbolic Model Checking , 2002, CAV.

[2]  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.

[3]  Radu Mateescu,et al.  Temporal logic patterns for querying dynamic models of cellular interaction networks , 2008, ECCB.

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

[5]  Valentin Goranko,et al.  Logic in Computer Science: Modelling and Reasoning About Systems , 2007, J. Log. Lang. Inf..

[6]  D. Bernardo,et al.  A Yeast Synthetic Network for In Vivo Assessment of Reverse-Engineering and Modeling Approaches , 2009, Cell.

[7]  John McGee,et al.  Discretization of Time Series Data , 2005, J. Comput. Biol..

[8]  J. Fromentin,et al.  Analysing Gene Regulatory Networks by both Constraint Programming and Model-Checking , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  Denis Thieffry,et al.  Qualitative Analysis of Regulatory Graphs: A Computational Tool Based on a Discrete Formal Framework , 2003, POSTA.

[10]  Laurent Trilling,et al.  Applications of a formal approach to decipher discrete genetic networks , 2010, BMC Bioinformatics.

[11]  Ilya Shmulevich,et al.  Binary analysis and optimization-based normalization of gene expression data , 2002, Bioinform..

[12]  Vincent Danos,et al.  Modeling and querying biomolecular interaction networks , 2004, Theor. Comput. Sci..

[13]  Adrien Richard,et al.  Negative circuits and sustained oscillations in asynchronous automata networks , 2009, Adv. Appl. Math..

[14]  René Thomas.  Regulatory networks seen as asynchronous automata: A logical description , 1991 .

[15]  Abdul Salam Jarrah,et al.  Parameter estimation for Boolean models of biological networks , 2009, Theor. Comput. Sci..