Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, CO, USA.
Interdisciplinary Computing and Complex Biosystems, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
Methods Mol Biol. 2024;2760:413-434. doi: 10.1007/978-1-0716-3658-9_23.
Flapjack presents a valuable solution for addressing challenges in the Design, Build, Test, Learn (DBTL) cycle of engineering synthetic genetic circuits. This platform provides a comprehensive suite of features for managing, analyzing, and visualizing kinetic gene expression data and associated metadata. By utilizing the Flapjack platform, researchers can effectively integrate the test phase with the build and learn phases, facilitating the characterization and optimization of genetic circuits. With its user-friendly interface and compatibility with external software, the Flapjack platform offers a practical tool for advancing synthetic biology research.This chapter provides an overview of the data model employed in Flapjack and its hierarchical structure, which aligns with the typical steps involved in conducting experiments and facilitating intuitive data management for users. Additionally, this chapter offers a detailed description of the user interface, guiding readers through accessing Flapjack, navigating its sections, performing essential tasks such as uploading data and creating plots, and accessing the platform through the pyFlapjack Python package.
Flapjack 为解决工程合成遗传回路的设计、构建、测试、学习 (DBTL) 周期中的挑战提供了有价值的解决方案。该平台提供了一套全面的功能，用于管理、分析和可视化动力学基因表达数据以及相关元数据。通过利用 Flapjack 平台，研究人员可以有效地将测试阶段与构建和学习阶段集成，促进遗传回路的表征和优化。Flapjack 平台具有用户友好的界面和与外部软件的兼容性，为推进合成生物学研究提供了实用工具。本章概述了 Flapjack 中使用的数据模型及其层次结构，该结构与进行实验和促进用户直观数据管理的典型步骤一致。此外，本章还详细描述了用户界面，指导读者访问 Flapjack、浏览其各个部分、执行上传数据和创建图等基本任务，以及通过 pyFlapjack Python 包访问该平台。
