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Browsing by Author "University of Minnesota Cellular Engineering Lab"

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    Cell-culture Data Pipeline Python package (CDPpy) for processing and analyzing cell culture datasets
    (2024-08-05) Lu, Yen-An; Fukae, Yudai; Hu, Wei-Shou; Zhang, Qi; qizh@umn.edu; Zhang, Qi; University of Minnesota Decision Discovery and Optimization Lab; University of Minnesota Cellular Engineering Lab
    CDPpy (Cell-culture Data Pipeline Python package) is an open-source library designed for the analysis of fed-batch cell culture data from multiple experiments and cell lines. The package features the functions of a data processing pipeline and visualization toolbox. The processing pipeline reads raw data from Excel files following a fixed template, derives variables such as cumulative substrate consumption and various specific rates, and exports the processed dataset into an Excel file. The specific rates show changing cellular activities over time in culture, providing insights for process optimization. The visualization toolbox enables users to analyze process profiles across experimental runs and cell lines, aiding in future experimental design. In this repository, we include the source code for the package, an instruction for package setup, and a Jupyter notebook that provides step-by-step guidelines for data processing and visualization using an example dataset. The updated version will be announced in the GitHub repository: https://github.com/ddolab/CDPpy in the future.