Model Checking Gene Regulatory Networks
نویسندگان
چکیده
The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs –an important problem of interest in evolutionary biology– more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.
منابع مشابه
H∞ Sampled-Data Controller Design for Stochastic Genetic Regulatory Networks
Artificially regulating gene expression is an important step in developing new treatment for system-level disease such as cancer. In this paper, we propose a method to regulate gene expression based on sampled-data measurements of gene products concentrations. Inherent noisy behaviour of Gene regulatory networks are modeled with stochastic nonlinear differential equation. To synthesize feed...
متن کاملParallel Model Checking Large-Scale Genetic Regulatory Networks with DiVinE
Studies of cells in silico can greatly reduce the need for expensive and prolonged laboratory experimentation. The use of model checking for the analysis of biological networks has attracted much attention recently. One of the practical limitations is the size of the model. In the paper we report on parallel model checking of genetic regulatory network using the model-checker DiVinE. The approa...
متن کاملAnalysis of Genetic Regulatory Networks: A Model-Checking Approach
Methods developed for the qualitative simulation of dynamical systems have turned out to be powerful tools for studying genetic regulatory networks. A bottleneck in the application of these methods is the analysis of the simulation results. In this paper, we propose a combination of qualitative simulation and model-checking techniques to perform this task systematically and efficiently. By mean...
متن کاملAn LTL Model Checking Approach for Biological Parameter Inference
The identification of biological parameters governing dynamics of Genetic Regulatory Networks (GRN) poses a problem of combinatorial explosion, since the possibilities of parameter instantiation are numerous even for small networks. In this paper, we propose to adapt LTL model checking algorithms to infer biological parameters from biological properties given as LTL formulas. In order to reduce...
متن کاملSpatial information to restrict the dynamics of genetic regulatory networks
In the course of understanding the functioning of cellular processes, modelling frameworks for biological networks are mandatory in order to reason on the models and their properties. One of the main problems with such modelling framework is to determine the dynamics of gene regulatory networks (GRN). Formal techniques, most of them based on model checking, have been applied to select valid dyn...
متن کامل