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000906596 1001_ $$0P:(DE-Juel1)174594$$aOsthege, Michael$$b0
000906596 245__ $$abletl ‐ A Python package for integrating BioLector microcultivation devices in the Design‐Build‐Test‐Learn cycle
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000906596 520__ $$aMicrobioreactor (MBR) devices have emerged as powerful cultivation tools for tasks of microbial phenotyping and bioprocess characterization and provide a wealth of online process data in a highly parallelized manner. Such datasets are difficult to interpret in short time by manual workflows. In this study, we present the Python package bletl and show how it enables robust data analyses and the application of machine learning techniques without tedious data parsing and preprocessing. bletl reads raw result files from BioLector I, II and Pro devices to make all the contained information available to Python-based data analysis workflows. Together with standard tooling from the Python scientific computing ecosystem, interactive visualizations and spline-based derivative calculations can be performed. Additionally, we present a new method for unbiased quantification of time-variable specific growth rate 
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000906596 7001_ $$0P:(DE-Juel1)168172$$aTenhaef, Niklas$$b1
000906596 7001_ $$0P:(DE-Juel1)173672$$aZyla, Rebecca$$b2
000906596 7001_ $$0P:(DE-Juel1)177776$$aMüller, Carolin$$b3
000906596 7001_ $$0P:(DE-Juel1)165723$$aHemmerich, Johannes$$b4
000906596 7001_ $$0P:(DE-Juel1)129076$$aWiechert, Wolfgang$$b5
000906596 7001_ $$0P:(DE-Juel1)129050$$aNoack, Stephan$$b6
000906596 7001_ $$0P:(DE-Juel1)129053$$aOldiges, Marco$$b7$$eCorresponding author
000906596 773__ $$0PERI:(DE-600)2071199-2$$a10.1002/elsc.202100108$$gp. elsc.202100108$$n3-4$$p242-259$$tEngineering in life sciences$$v22$$x1618-0240$$y2022
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