Ralf Zimmer

Fuzzifier* provides a differential analysis framework for multi-omics data, identifying reliable and sensitive features by analyzing value distributions and foldchange patterns across groups.

The paper maps immune cell trajectories and interactions in human thrombi, identifying prothrombotic and thrombolytic monocyte and neutrophil subsets with therapeutic implications.

The paper introduces mx-plore, a database of miRNA-gene interactions derived from text mining, providing context-specific information from scientific publications.

The paper introduces MS-EmpiReS, a method to detect differential alternative splicing in proteomics data, identifying cancer-relevant splicing candidates and showing correlation with RNA sequencing.

The paper identifies proteins related to the bacterial envelope that improve starvation survival in E. coli by analyzing proteome adaptation across multiple conditions.

EmpiReS improves detection of differentially expressed and alternatively spliced genes using fold change analysis with empirical error estimation.

The paper benchmarks gene set enrichment methods using a curated compendium of disease datasets, identifying performance differences and providing recommendations for improved analysis.

MS-EmpiRe improves detection of differentially abundant proteins by using peptide-level noise distributions, doubling correct identifications at FDR cutoffs compared to existing tools.

The paper introduces a method to improve spectral library coverage in DIA proteomics by using multiple characteristic intensity patterns, achieving near-complete coverage without increasing false discovery rates.