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Data and code to the paper "Bayesian calibration, process modeling and uncertainty quantification in biotechnology".

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This repository contains the raw data and analysis that are the supporting information to the calibr8 paper.

Contents

The material is organized by the chapter of first appearance in the manuscript. The raw_data directory contains unprocessed result files.

Some of the MCMC trace files (*.nc) exceed GitHub's file upload size limit. We therefore decided to upload the *.nc files through releases.

Installation

A Python environment for running the notebooks can be created with the following command:

conda env create -f environment.yml

The new environment is named murefi_env and can be activated with conda activate murefi_env.

After that a Jupyter notebook server can be launched with jupyter notebook.

Note: The only notebook not executable is 0.0 Preprocessing.ipynb. This notebook relies on unpublished software. However, all processed data is included as XLSX or HDF5 files in the processed directory and the data analysis can be re-run accordingly.

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Data and code to the paper "Bayesian calibration, process modeling and uncertainty quantification in biotechnology".

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