%0 Generic
%A Zegers, Marika
%A Roy, Moumita
%A Jourdin, Ludovic
%D 2025
%T Dataset for 'Identifying Key Drivers of Product Formation in Microbial Electrosynthesis with a Mixed Linear Regression Analysis'
%U 
%R 10.4121/5e840d08-55f6-4daa-a639-048cebcd8266.v1
%K Microbial electrosynthesis
%K CO2 valorisation
%K Biofilm
%K Mixed culture
%K Carboxylic acids
%K Chain elongation
%K Statistical analysis
%K Design of experiments
%K Mixed linear regression modelling
%K Reactor variance
%X <p>The analysed data and complete scripts for the permutation tests and mixed linear regression models (MLRMs) used in the paper 'Identifying Key Drivers of Product Formation in Microbial Electrosynthesis with a Mixed Linear Regression Analysis'.</p><p>Python version 3.10.13 with packages numpy, pandas, os, scipy.optimize, scipy.stats, sklearn.metrics, matplotlib.pyplot, statsmodels.formula.api, seaborn are required to run the .py files. Ensure all packages are installed before running the scripts. Data files required to run the code (.xlsx and .csv format) are included in the relevant folders.</p>
%I 4TU.ResearchData