Author

Luc A. C. Pieters

University of AntwerpORCID 0000-0002-8288-4254Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metabolomics· 2 Research Focus:benchmarking· 1 Research Focus:dimensionality reduction· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Adrian CovaciiD· 2 shared Charlie BeirnaertiD· 2 shared Kris LaukensiD· 2 shared Pieter MeysmaniD· 2 shared Anastasia Van der Auwera· 1 shared Deborah Custers· 1 shared Kenn FoubertiD· 1 shared Laura PeetersiD· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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2 shared papersBioinformatics

Adrian CovaciORCID

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2 papers

Recent·Most cited

Using expert driven machine learning to enhance dynamic metabolomics data analysis.

Charlie Beirnaert, Laura Peeters, Pieter Meysman, Wout Bittremieux, Kenn Foubert, Deborah Custers, Anastasia Van der Auwera, Matthias Cuykx, Luc A. C. Pieters, Adrian Covaci, Kris Laukens

This paper introduces a tool that uses expert knowledge in machine learning to analyze dynamic metabolomics data, showing it performs as well as statistical methods.

Metabolites · Mar 20, 2019Peer-reviewedBioinformatics

speaq 2.0: a complete workflow for high-throughput 1D NMR spectra processing and quantification

Charlie Beirnaert, Pieter Meysman, Trung Nghia Vu, Nina Hermans, Sandra Apers, Luc A. C. Pieters, Adrian Covaci, Kris Laukens

speaq 2.0 automates 1D NMR spectral processing and quantification, reducing user interaction and enabling reproducible metabolomics analysis.

PLoS Computational Biology · Mar 1, 2018Peer-reviewedBioinformatics