Abstract
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.
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References
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Vitalis, C. et al. (2024). Flapjack: Data Management and Analysis for Genetic Circuit Characterization. In: Braman, J.C. (eds) Synthetic Biology. Methods in Molecular Biology, vol 2760. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3658-9_23
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DOI: https://doi.org/10.1007/978-1-0716-3658-9_23
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