Philipp Sven Lars Schäfer

The paper benchmarks computational models predicting B. pertussis booster vaccine responses using multi-omics data from three cohorts, identifying key predictors of immunity and establishing a community resource for systems vaccinology.

The paper evaluates single-cell perturbation prediction models by developing a taxonomy and tool to standardize benchmarking protocols across datasets.

ParTIpy scales archetypal analysis for biological trade-offs and integrates with single-cell workflows, enabling task inference in large datasets.

This paper constructs a transcriptional patient map of SLE using single-cell and bulk RNA-seq data, identifying conserved immune programs in blood and kidney tissue.

This study identifies conserved and diverged gene regulatory networks in mammalian cerebellum development using single-nucleus gene expression and chromatin accessibility data from six species.

This study identifies cell-state plasticity as a driver of heterogeneity in Group 3/4 medulloblastomas, showing that transcription factor perturbation can redirect tumor cells along different differentiation trajectories.

LIANA+ is a framework for analyzing cell-cell communication in single-cell and spatial transcriptomics data, integrating multiple methods and supporting multi-omics data.