Model checking the evolution of gene regulatory networks
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Author
Corresponding author has ISTA affiliation
Department
Grant
Quantitative Reactive Modeling
Rigorous Systems Engineering
Formal methods for the design and analysis of complex systems
Speed of Adaptation in Population Genetics and Evolutionary Computation
International IST Postdoc Fellowship Programme
Limits to selection in biology and in evolutionary computation
Rigorous Systems Engineering
Formal methods for the design and analysis of complex systems
Speed of Adaptation in Population Genetics and Evolutionary Computation
International IST Postdoc Fellowship Programme
Limits to selection in biology and in evolutionary computation
Abstract
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 logic. 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.
Publishing Year
Date Published
2017-12-01
Journal Title
Acta Informatica
Publisher
Springer
Volume
54
Issue
8
Page
765 - 787
ISSN
IST-REx-ID
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