AMLab | Amsterdam Machine Learning Lab

Jim Boelrijk

PhD candidate (advised by Patrick Forré, Bob Pirok, Bernd Ensing, and Alfons Hoekstra)
AMLab and AI4Science Lab
Institute of Informatics
University of Amsterdam
Science Park 904, C3.230

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I am a PhD student at the Amsterdam Machine Learning Lab (AMLab) and the AI4Science Lab. I collaborate with the Chemometrics and Advanced Seperations Team (CAST) and the Computational Chemistry group at the Van ‘t Hoff Institute for Molecular Sciences (HIMS). Current research focuses on tailored Bayesian optimization methods for automation and using machine learning to identify structure-property relationships in molecular data.

Selected Publications

Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data

Boelrijk, Jim, Herwerden, Denice, Samanipour, Saer, Ensing, Bernd, and Forré, Patrick

Jul 2022

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Non-target analysis combined with high resolution mass spectrometry is considered one of the most comprehensive strategies for the detection and identification of known and unknown chemicals in complex samples. However, many compounds remain unidentified due to data complexity and limited structures in chemical databases. In this work, we have developed and validated a novel machine learning algorithm to predict the retention index (r_i) values for structurally (un)known chemicals based on their measured fragmentation pattern. The developed model, for the first time, enabled the predication of r_i values without the need for the exact structure of the chemicals, with an R^2 of 0.91 and 0.77 and root mean squared error (RMSE) of 47 and 67 r_i units for the Norman and amide test set, respectively. This fragment based model showed comparable accuracy in r_i prediction compared to conventional descriptor-based models that rely on known chemical structure, which obtained a R^2 of 0.85 with and RMSE of 67.
Bayesian optimization of comprehensive two-dimensional liquid chromatography separations

Boelrijk, Jim, Pirok, Bob, Ensing, Bernd, and Forré, Patrick

Journal of Chromatography A Jul 2021

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