Interdisciplinary Computing and Complex Biosystems, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, CO, USA.
Methods Mol Biol. 2024;2760:393-412. doi: 10.1007/978-1-0716-3658-9_22.
Genetic design automation (GDA) is the use of computer-aided design (CAD) in designing genetic networks. GDA tools are necessary to create more complex synthetic genetic networks in a high-throughput fashion. At the core of these tools is the abstraction of a hierarchy of standardized components. The components' input, output, and interactions must be captured and parametrized from relevant experimental data. Simulations of genetic networks should use those parameters and include the experimental context to be compared with the experimental results.This chapter introduces Logical Operators for Integrated Cell Algorithms (LOICA), a Python package used for designing, modeling, and characterizing genetic networks using a simple object-oriented design abstraction. LOICA represents different biological and experimental components as classes that interact to generate models. These models can be parametrized by direct connection to the Flapjack experimental data management platform to characterize abstracted components with experimental data. The models can be simulated using stochastic simulation algorithms or ordinary differential equations with varying noise levels. The simulated data can be managed and published using Flapjack alongside experimental data for comparison. LOICA genetic network designs can be represented as graphs and plotted as networks for visual inspection and serialized as Python objects or in the Synthetic Biology Open Language (SBOL) format for sharing and use in other designs.
遗传设计自动化（GDA）是在设计遗传网络中使用计算机辅助设计（CAD）。GDA 工具对于以高通量方式创建更复杂的合成遗传网络是必要的。这些工具的核心是标准化组件层次结构的抽象。组件的输入、输出和相互作用必须从相关的实验数据中捕获和参数化。遗传网络的模拟应该使用这些参数，并包括实验上下文，以便与实验结果进行比较。
本章介绍了用于设计、建模和表征遗传网络的 Python 包 Logical Operators for Integrated Cell Algorithms (LOICA)，该包使用简单的面向对象设计抽象来实现。LOICA 将不同的生物和实验组件表示为类，这些类相互作用以生成模型。这些模型可以通过直接连接到 Flapjack 实验数据管理平台进行参数化，以使用实验数据对抽象组件进行特征化。可以使用随机模拟算法或具有不同噪声水平的常微分方程对模型进行模拟。可以使用 Flapjack 管理和发布模拟数据以及实验数据，以便进行比较。LOICA 遗传网络设计可以表示为图形，并绘制为网络进行可视化检查，并序列化 Python 对象或在 Synthetic Biology Open Language (SBOL) 格式中进行序列化，以便在其他设计中共享和使用。
