Sandra Götze

The paper identifies cell type-specific lipid and protein compositions of apoE lipoproteins secreted by different brain cell types and found in cerebrospinal fluid.

This paper introduces a normalization framework to decouple protocol and instrument effects in multicenter proteomics studies, demonstrating its application to the PME13 dataset.

The paper integrates multi-omics data from pediatric sepsis patients to identify a reproducible inflammatory host-response axis associated with disease severity.

MOAgent discovers biomarker candidates in multi-omics data using gradient-boosted decision trees, addressing data challenges and providing accessible analysis tools.

The paper identifies a cell surface protein complex, the HDL synapse, that modulates HDL uptake into endothelial cells, with AMPN playing a key role.

The paper identifies HDL receptors and their interactions in human endothelial cells, revealing MERTK as a novel co-receptor for HDL binding and uptake.

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

This paper standardizes a proteotype analysis workflow across multiple international sites to enable distributed, reproducible proteomic data generation for precision medicine.

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.

The paper develops a DIA-based proteotyping strategy for HDL particles, revealing significant proteotype differences between healthy individuals and those with T2DM or CHD.

The paper develops a proteogenomic resource for Listeria monocytogenes to analyze genotype-proteotype-phenotype relationships using proteotyping and genomic databases.

The paper develops an integrative proteogenomics strategy to improve prokaryotic genome annotation by combining multiple resources and experimental data, identifying novel ORFs and correcting errors.