Software

• transreg: Transfer learning (CRAN)

• cornet: Dichotomised Outcome Regression (CRAN)

• joinet: Multivariate Prediction (CRAN)

• starnet: Stacked Elastic Net (CRAN)

• palasso: Paired Lasso Regression (CRAN)

• semisup: Semi-Supervised Mixture Test (Bioconductor)

• globalSeq: Global Test for Counts (Bioconductor)

Manuscripts

• Rauschenberger A, Landoulsi Z, van de Wiel MA, and Glaab E (2023). “Penalised regression with multiple sources of prior effects”. Bioinformatics doi: 10.1093/bioinformatics/btad680.

• Rauschenberger A, and Glaab E (2023). “Predicting dichotomised outcomes from high-dimensional data in biomedicine”. Journal of Applied Statistics. doi: 10.1080/02664763.2023.2233057.

• Rauschenberger A, and Glaab E (2021). “Predicting correlated outcomes from molecular data”. Bioinformatics 37(21):3889–389. doi: 10.1093/bioinformatics/btab576.

• 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.

• 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.

• 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.

• 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.