Jeffrey M. Spraggins

The paper develops an optimized multimodal imaging workflow that preserves tissue integrity and enables comprehensive profiling of morphology, collagen, cell populations, N-glycans, and extracellular matrix peptides from a single tissue section.

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

This study uses spatial transcriptomics to analyze gene expression in heart transplant recipients during rejection, identifying distinct transcriptomic profiles associated with different rejection types and outcomes.

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.

CelLink integrates single-cell multi-omics data by addressing weak feature linkage and imbalanced cell populations, outperforming existing methods in imputation accuracy and cell subtype annotation.

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

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 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.

The paper introduces MILWRM, a tool for detecting tissue domains in spatial-omics data, and demonstrates its application in human colonic polyps and mouse brain slices.

This study identifies GNASR201C as a driver of pyloric metaplasia in IPMN, characterized by tumor-suppressive glycans that inhibit cancer progression.

The paper evaluates five algorithms for segmenting functional tissue units in kidney and colon tissues using histological stains, comparing their accuracy and generalizability.

The paper presents software tools and user interfaces for annotating and exploring tissue data in a human reference atlas, enabling data harmonization and public access.

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.