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sparselink: Sparse regression for related problems (CRAN)
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semisup: Semi-Supervised Mixture Test (Bioconductor)
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globalSeq: Global Test for Counts (Bioconductor)
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Rauschenberger A, Nazarov PN, and Glaab E (2025). "Estimating sparse regression models in multi-task learning and transfer learning through adaptive penalisation". Bioinformatics 41(10):btaf406. doi: 10.1093/bioinformatics/btaf406.
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Rauschenberger A, Landoulsi Z, van de Wiel MA, and Glaab E (2023). "Penalised regression with multiple sources of prior effects". Bioinformatics 39(12):btad680. doi: 10.1093/bioinformatics/btad680.
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Rauschenberger A, and Glaab E (2024). "Predicting dichotomised outcomes from high-dimensional data in biomedicine". Journal of Applied Statistics 51(9):1756-1771. doi: 10.1080/02664763.2023.2233057.
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Rauschenberger A, and Glaab E (2021). "Predicting correlated outcomes from molecular data". Bioinformatics 37(21):3889–3895. doi: 10.1093/bioinformatics/btab576.
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Rauschenberger A, Glaab E, and van de Wiel MA (2021). "Predictive and interpretable models via the stacked elastic net". Bioinformatics 37(14):2012–2016. doi: 10.1093/bioinformatics/btaa535.
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Rauschenberger A, Ciocanea-Teodorescu I, Menezes RX, Jonker MA, and van de Wiel MA (2020). "Sparse classification with paired covariates". Advances in Data Analysis and Classification 14:571–588. doi: 10.1007/s11634-019-00375-6.
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Rauschenberger A, Menezes RX, van de Wiel MA, van Schoor NM, and Jonker MA (2018). "Detecting SNPs with interactive effects on a quantitative trait". arXiv: 1805.09175.
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Rauschenberger A, Jonker MA, van de Wiel MA, and Menezes RX (2016). "Testing for association between RNA-Seq and high-dimensional data". BMC Bioinformatics 17:118. doi: 10.1186/s12859-016-0961-5.
For applied projects, see ORCiD or Google Scholar.