growthcurves: User-friendly tools for quality-controlled cellular growth analysis
Bradley, S. A.; Webel, H.; Donati, S.; Acevedo-Rocha, C.
Show abstract
SummaryBiological 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, that combine automated fitting with interactive, human-in-the-loop inspection, selective refitting and traceable export for microplate reader and mini-bioreactor datasets in batch or turbidostat cultivation mode. Availability and Implementationgrowthcurves is implemented in Python and is freely available to non-commercial users at [https://github.com/biosustain/growthcurves.git] and through PyPI at [https://pypi.org/project/growthcurves/]. MicroGrowth and AutoGrowth are available at [https://biosustain.github.io/growthcurves_app/], and their source code is available at [https://github.com/biosustain/growthcurves_app.git]. Documentation, installation instructions, example datasets and tutorials are available at [https://growthcurves.readthedocs.io/en/latest/]. Contactstefdon@dtu.dk; cargac@dtu.dk Supplementary InformationSupplementary information and Supplementary Methods are available online.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.