Automated Synthesis and Analysis of Switching Gene Regulatory Networks

Studying the gene regulatory networks (GRNs) that govern how cells change into specific cell types with unique roles throughout development is an active area of experimental research. The fate specification process can be viewed as a biological program prescribing the system dynamics, governed by a...

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Bibliographic Details
Published in:BioSystems 2016-08, Vol.146, p.26-34
Main Authors: Shavit, Yoli, Yordanov, Boyan, Dunn, Sara-Jane, Wintersteiger, Christoph M., Otani, Tomoki, Hamadi, Youssef, Livesey, Frederick J., Kugler, Hillel
Format: Article
Language:English
Subjects:
Algorithms
Animals
Biological modelling
Boolean networks (BNs)
Cell Differentiation - genetics
Cell fate
Computational Biology - methods
Computer Simulation
Gene regulatory networks (GRNs)
Gene Regulatory Networks - genetics
Humans
Mammalian cortex
Models, Genetic
Nerve Net - metabolism
Neurons - cytology
Neurons - metabolism
Satisfiability Modulo Theories (SMT)
Self-modifying code
Synthesis
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Summary:Studying the gene regulatory networks (GRNs) that govern how cells change into specific cell types with unique roles throughout development is an active area of experimental research. The fate specification process can be viewed as a biological program prescribing the system dynamics, governed by a network of genetic interactions. To investigate the possibility that GRNs are not fixed but rather change their topology, for example as cells progress through commitment, we introduce the concept of Switching Gene Regulatory Networks (SGRNs) to enable the modelling and analysis of network reconfiguration. We define the synthesis problem of constructing SGRNs that are guaranteed to satisfy a set of constraints representing experimental observations of cell behaviour. We propose a solution to this problem that employs methods based upon Satisfiability Modulo Theories (SMT) solvers, and evaluate the feasibility and scalability of our approach by considering a set of synthetic benchmarks exhibiting possible biological behaviour of cell development. We outline how our approach is applied to a more realistic biological system, by considering a simplified network involved in the processes of neuron maturation and fate specification in the mammalian cortex.
ISSN:0303-2647
1872-8324
DOI:10.1016/j.biosystems.2016.03.012