The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/0c67a2a7-3ead-4f1d-acac-9e1ef843d0d2

Neijenhuis, Tim (2025): Data accompanying the PhD dissertation "Structure-Based Prediction of Protein Behavior in Preparative Chromatography". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0c67a2a7-3ead-4f1d-acac-9e1ef843d0d2.v1

Categories

• Human Pharmaceutical Products
• Engineering
• Manufacturing
• Biological Sciences

Keywords

Chromatography machine learning Multiple linear regression Protein Protein structure

Licence

CC BY-NC-ND 4.0

Interoperability

• RO-Crate Metadata

Export as...

RefWorks BibTeX Reference Manager Endnote DataCite NLM DC CFF

by Tim Neijenhuis

This repository contains the data generated during the PhD project: Structure-Based Prediction of Protein Behavior in Preparative Chromatography

By Tim Neijenhuis in Delft University of Technology

Supervisors: Marcel Ottens and Marieke Klijn

Department of Biotechnology, Section of Bioprocess Engineering.

When using the data, please refer using:

Neijenhuis, T., Le Bussy, O., Geldhof, G., Klijn, M. E., & Ottens, M. (2024). Predicting protein retention in ion‐exchange chromatography using an open source QSPR workflow. Biotechnology Journal, 19(3), 2300708.

Keulen, D., Neijenhuis, T., Lazopoulou, A., Disela, R., Geldhof, G., Le Bussy, O., ... & Ottens, M. (2025). From protein structure to an optimized chromatographic capture step using multiscale modeling. Biotechnology Progress, 41(1), e3505.

Disela, R., Neijenhuis, T., Le Bussy, O., Geldhof, G., Klijn, M., Pabst, M., & Ottens, M. (2024). Experimental characterization and prediction of Escherichia coli host cell proteome retention during preparative chromatography. Biotechnology and Bioengineering, 121(12), 3848-3859.

The objective of the PhD project was to predict the behavior of proteins for different chromatographic columns using molecular modeling methods.

This repository contains all predicted and measured values for each protein for the different columns investigated during the research in a CSV format.

These name of each file is identical to the figure presented in the dissertation stating first the chapter followed by the figure (as {chapter}_data_{figure}.csv).

History

• 2025-07-08 first online, published, posted

Publisher

4TU.ResearchData

Format

.csv

Funding

• Dutch Ministry of Economic Affairs of The Netherlands via the Top Consortium for Knowledge and Innovation (TKI) roadmap Chemistry of Life (grant code CHEMIE.PGT.2021.015)
• GlaxoSmitKline Biologicals S.A.

Organizations

TU Delft, Faculty of Applied Sciences, Department of Biotechnology, Bioprocess Engineering