Author

Thijs Nieuwkoop

Wageningen University & ResearchORCID 0000-0002-1969-3084Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Molecular Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Organism:E. coli· 2 Approach:machine learning (classical)· 2 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Barbara R. TerlouwiD· 2 shared John van der OOSTiD· 2 shared Nico J. ClaassensiD· 2 shared Charlotte C. KosteriD· 1 shared Dick de RidderiD· 1 shared Hans G. H. J. HeiligiD· 1 shared María Martín‐PascualiD· 1 shared Miguel Paredes-BarradaiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersMolecular Biology

Barbara R. TerlouwORCID

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2 papers

Recent·Most cited

Molecular BiologybioRxivPreprintJul 7, 2026

Systematic engineering and machine learning analysis of intrinsic terminators reveal crucial nucleotides directly upstream of the terminator hairpin.

Charlotte C. Koster, Barbara R. Terlouw, Thijs Nieuwkoop…·Nico J. Claassens

The paper systematically engineers and analyzes intrinsic terminators in bacteria, finding that an adenosine upstream of the terminator hairpin improves protein production and reduces read-through.

DOI 10.64898/2026.07.06.736697

E. coliDNA methylation

𝕏 PostBluesky

Molecular BiologybioRxivPreprintApr 5, 2022

Revealing determinants of translation efficiency via whole-gene codon randomisation and machine learning

Thijs Nieuwkoop, Barbara R. Terlouw, Dick de Ridder…·Nico J. Claassens

This study uses codon randomisation and machine learning to show that the first 8 codons of a gene strongly predict protein production levels in E. coli.

DOI 10.1101/2022.04.05.486962

E. coliwhole-genome sequencing

𝕏 PostBluesky