Lukasz G. Migas

IsoMobil reduces high-dimensional ion mobility mass spectrometry data by grouping isotopologues, improving interpretation at the molecular-species level.

The paper maps lipid microenvironments in human brain vasculature using multimodal imaging and identifies lipid markers associated with cerebral amyloid angiopathy.

This study identifies region-specific lipid alterations in Alzheimer’s disease white matter hyperintensities using multimodal imaging and SHAP analysis.

The paper introduces a method to uncover molecular substructures in human kidney tissue using signal strength-aware latent spaces, revealing previously unknown lipid species and biological subdivisions.

IsoSpace provides a chemistry-informed dimensionality reduction method for imaging mass spectrometry that identifies isotopic patterns without prior assumptions.

This paper introduces TULIP, a method to unmix IMS data using microscopy constraints, improving analysis of tissue structures in synthetic and kidney datasets.

The paper introduces Moran quadrant maps and workflows for spatial-statistical analysis of molecular imaging data, enabling scalable exploration of spatial dependence and heterogeneity.

This paper introduces a multimodal pipeline for spatiomolecular analysis of tissue samples, demonstrating its application in Alzheimer's disease and type 2 diabetes.

The paper introduces a data reduction method for imaging mass spectrometry that preserves full spectrum information while achieving size reduction comparable to traditional methods.

The paper develops a multimodal imaging pipeline to identify molecular markers of cellular neighborhoods in human kidney tissue by integrating imaging mass spectrometry and immunofluorescence data.

This paper integrates MALDI IMS and MxIF microscopy to analyze lipid and molecular profiles of glomerular cell types and substructures in human kidney tissue.

msiFlow automates and streamlines multimodal mass spectrometry imaging and immunofluorescence data analysis to enhance reproducibility and scalability in biological research.

This paper introduces an automated workflow using SHAP to identify biomarker candidates in imaging mass spectrometry data by ranking molecular species based on their predictive importance for biological class recognition.

This study evaluates how molecular conformation, partial charges, and basis sets affect collision cross sections of monosaccharides calculated from DFT conformers compared to experimental values.