Dušan Veličković

This study identifies cell-type-specific carbon metabolism changes in poplar under combined abiotic stresses using multi-omics approaches.

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

The paper evaluates a TT8 knockout mutant in pennycress, finding loss of proanthocyanidins in seed coats and increased seed imbibition rates without agronomically detrimental effects.

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 study maps how endophytes alter root metabolism under drought using chemical imaging and machine learning, identifying metabolites as indicators of drought and endophyte presence.

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

This paper develops a spatial proteomics workflow to identify and map proteoforms in human kidney tissue, revealing spatially distinct proteomic profiles between glomeruli and tubules.

The paper investigates microbial interactions in algal systems, finding that cooperation, not just competition, significantly influences carbon flow from algae to bacteria.

This study examines spatiotemporal metabolic responses to water deficit stress in poplar leaf cell types using MALDI-MSI, revealing distinct metabolic shifts in palisade and vascular cells.

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

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.