Shavit Yoli, Yordanov Boyan, Dunn Sara-Jane, Wintersteiger Christoph M, Otani Tomoki, Hamadi Youssef, Livesey Frederick J, Kugler Hillel
University of Cambridge, UK; Microsoft Research, UK.
Microsoft Research, UK.
Biosystems. 2016 Aug;146:26-34. doi: 10.1016/j.biosystems.2016.03.012. Epub 2016 May 10.
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.
研究基因调控网络（GRNs），这些网络控制着细胞在整个发育过程中如何转变为具有独特功能的特定细胞类型，是实验研究的一个活跃领域。命运指定过程可以被视为一个规定系统动态的生物学程序，由遗传相互作用网络控制。为了研究基因调控网络不是固定不变而是会改变其拓扑结构的可能性，例如随着细胞通过承诺阶段的进展，我们引入了切换基因调控网络（SGRNs）的概念，以实现对网络重新配置的建模和分析。我们定义了构建SGRNs的合成问题，这些SGRNs保证满足一组代表细胞行为实验观察的约束条件。我们提出了一种解决这个问题的方法，该方法采用基于可满足性模理论（SMT）求解器的方法，并通过考虑一组展示细胞发育可能生物学行为的合成基准来评估我们方法的可行性和可扩展性。我们概述了如何通过考虑参与哺乳动物皮层神经元成熟和命运指定过程的简化网络，将我们的方法应用于更现实的生物系统。
