T.O. Mokveld, Z. Al-Ars, Erik A. Sistermans, M.J.T. Reinders (2023), A comprehensive performance analysis of sequence-based within-sample testing NIPT methods, In PLoS ONE Volume 18.

Michiel Bongaerts, Purva Kulkarni, Alan Zammit, Ramon Bonte, Leo A. J. Kluijtmans, Henk J. Blom, Udo F. H. Engelke, D.M.J. Tax, George J.G. Ruijter, M.J.T. Reinders (2023), Benchmarking Outlier Detection Methods for Detecting IEM Patients in Untargeted Metabolomics Data, In Metabolites Volume 13.

Niccolo' Tesi, Sven van der Lee, Marc Hulsman, Henne Holstege, Marcel Reinders (2023), Bioinformatics Strategies for the Analysis and Integration of Large-Scale Multiomics Data, The journals of gerontology. Series A, Biological sciences and medical sciences Volume 78 p.659-662.

Pia Keukeleire, Stavros Makrodimitris, Marcel Reinders (2023), Cell type deconvolution of methylated cell-free DNA at the resolution of individual reads, In NAR Genomics and Bioinformatics Volume 5.

Kirti Biharie, Lieke Michielsen, Marcel J.T. Reinders, Ahmed Mahfouz (2023), Cell type matching across species using protein embeddings and transfer learning, In Bioinformatics (Oxford, England) Volume 39 p.i404-i412.

Gerard A. Bouland, Ahmed Mahfouz, Marcel J.T. Reinders (2023), Consequences and opportunities arising due to sparser single-cell RNA-seq datasets, In Genome biology Volume 24.

M. Zhang, G.A. Bouland, H. Holstege, M.J.T. Reinders (2023), Identifying Aging and Alzheimer Disease–Associated Somatic Variations in Excitatory Neurons From the Human Frontal Cortex, In Neurology: Genetics Volume 9 p.1-12.

Elisabeth M. Jongbloed, Maurice P.H.M. Jansen, Vanja de Weerd, Jean A. Helmijr, Corine M. Beaufort, Marcel J.T. Reinders, Ronald van Marion, Wilfred F.J. van IJcken, Stavros Makrodimitris (2023), Machine learning-based somatic variant calling in cell-free DNA of metastatic breast cancer patients using large NGS panels, In Scientific Reports Volume 13.

Soufiane M.C. Mourragui, Marco Loog, Mirrelijn van Nee, Mark A.van de Wiel, Marcel J.T. Reinders, Lodewyk F.A. Wessels (2023), Percolate: An Exponential Family JIVE Model to Design DNA-Based Predictors of Drug Response, Haixu Tang (Eds.), In Research in Computational Molecular Biology - 27th Annual International Conference, RECOMB 2023, Proceedings p.120-138, Springer.

Ramin Ghorbani, Marcel J.T. Reinders, David M.J. Tax (2023), Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability, In ICMLT 2023 - Proceedings of 2023 8th International Conference on Machine Learning Technologies p.127-132, Association for Computing Machinery (ACM).