Jan Baumbach

BoostDiff identifies differential gene regulatory networks between disease and healthy states, outperforming existing methods on simulated and real transcriptomics data.

The paper introduces dsMTL, a framework for privacy-preserving, distributed multi-task machine learning, and evaluates its performance in identifying biological signatures across distributed datasets.

Namco provides a user-friendly R Shiny application for comprehensive microbiome analysis, covering data processing to complex tasks like machine learning and network analysis.

DICAST benchmarks alternative splicing analysis tools, showing STAR and HISAT2 perform best, and proposes a reporting standard for event detection.

MoSBi automates biclustering analysis across multi-omics data to identify robust molecular signatures for stratification and subtyping.

The paper identifies co-translational assembly domains in proteins that facilitate interactions between nascent chains and fully synthesized subunits, revealing their role in regulating complex assembly pathways.

The paper introduces NEASE, a tool for functional analysis of alternative splicing events, showing its ability to identify pathways related to tissue identity and cell type development, and highlight splicing-related biomarkers.

The paper compares differential expression analysis methods for CyTOF data, finding that median-based methods are reliable for non-zero-inflated data while methods using full distributions handle zero-inflation better but may overpredict.

The paper identifies a genetic variant in FBLN1 associated with nonverbal reasoning and links it to pathways, cell types, and diseases involved in cognition.

BiCoN identifies patient subgroups and functional gene subnetworks by integrating network constraints with biclustering of omics data.

DeepCLIP predicts the functional effects of nucleotide variants on protein-RNA binding using sequence data and outperforms existing methods in classification and experimental validation.

sPLINK enables federated GWAS on distributed datasets without data sharing, preserving privacy and accuracy while being robust to heterogeneity.

The paper introduces Scellnetor, a tool to identify systems biology patterns in pseudo-temporal trajectories from scRNA-seq data, applied to hematopoiesis and CD8 T-cell development.

The paper introduces the MS Atlas, a molecular map of brain lesion stages in progressive multiple sclerosis, providing transcriptomic profiles and tools for analysis.

The paper identifies age-related DNA methylation patterns on the X-chromosome in males and females and finds sex differences in their association with mortality.

The paper evaluates computational methods for estimating immune-cell composition from bulk RNA-seq data using simulated and real datasets, finding high accuracy for well-defined cell-type signatures.