Biological growth curves are widely used but inconsistently analyzed due to fragmented workflows and limited quality control. We present growthcurves, a Python package for extracting growth parameters, and two open-source web applications (MicroGrowth and AutoGrowth) enabling human-in-the-loop analysis of datasets from microplate reader or mini-bioreactor experiments in either batch or turbidostat cultivation mode. By combining automated fitting with convenient quality control, the platform improves reproducibility and reliability of growth-curve analysis.
Bradley, S. A., Webel, H., Donati, S., Acevedo-Rocha, C.
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