As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information.

中文翻译：

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遗传电路设计的网络方法

随着基因电路变得越来越复杂，有关其设计的数据的大小和复杂性也在增加。捕获的这些数据超越了单片基因序列，并针对电路模块化和功能细节，这有利于分析电路性能和建立设计自动化技术。然而，迄今为止，设计数据（和元数据）的可访问性、可视化和可用性受到的关注相对较少。在这里，我们提出了一种将电路设计转变为网络的方法，并展示了其增强设计数据效用的潜力。由于网络是动态结构，因此可以根据抽象、层次结构和蛋白质相互作用等要求，将初始图交互地塑造成相关信息的子网络。此外，可以应用几个视觉变化，例如基于类型（例如基因或启动子）的着色或聚类节点，从而从用户的角度更容易理解。这种方法允许电路设计与其他网络耦合，例如代谢途径或以类似图形格式捕获的实现协议。因此，我们提倡使用网络来构建、访问和改进合成生物学信息。