Christopher Anderton

The paper introduces RomicsProcessor, a reproducible-by-design tool for multi-omics and spatial-omics analysis that enforces FAIR principles and ensures computational reproducibility.

This paper uses spatial microproteomics to characterize the proteomic landscape of Bacillus subtilis biofilms, identifying subpopulations through proteoform analysis.

This study identifies a MEF2C transcription factor network that regulates endothelial cell proliferation in diabetic kidney disease and shows that SGLT2i treatment can reverse its dysregulation.

The paper presents a multi-modal atlas of human kidney disease, identifying cellular and spatial mechanisms of injury resolution or failure and linking them to clinical outcomes.

This paper presents a multimodal imaging approach to characterize metabolic changes in bronchopulmonary dysplasia, revealing altered lipid distributions and collagen remodeling in affected tissues.

The paper integrates N-glycan analysis with CODEX imaging to identify cell-specific glycosylation patterns in healthy human lung tissue.

The paper evaluates spatial metabolomics protocols and technologies, showing extensive metabolite coverage and comparable results across imaging MS methods.

The paper creates a high-resolution cellular atlas of healthy and injured kidney cell states and niches using single-cell and spatial technologies, identifying molecular signatures and pathways related to kidney injury.

The paper constructs a reference tissue atlas of the human kidney using multi-omics data to identify cell types, pathways, and genes across nephron segments and interstitium.

An open-source cloud engine annotates imaging mass spectrometry data at controlled false discovery rate; publicly shared results reached over 3200 datasets and 6 million metabolite images by January 2019.