Parker C. Wilson

This paper introduces a measure of transcriptional dyscoordination to quantify aging in single cells, showing it increases with age and is linked to cellular processes like senescence and genome instability.

This paper identifies context geometry compression in virtual cell models and shows that recoverable biological resolution, not measurement dimensionality, determines the accuracy of perturbation-response predictions.

The paper identifies Intervention Geometry Compression (IGC) in virtual-cell models, showing that high state similarity can mask loss of perturbation relationships, and proposes empirical anchoring to improve generalization.

This paper introduces TraceBIND, a method to correct Tn5 bias in ATAC-seq data, improving TF footprint detection and revealing age-related regulatory changes in scATAC-seq.

S2Omics automatically selects regions of interest from histology images to maximize molecular information content in spatial omics experiments, improving reproducibility and downstream biological discovery.

The paper introduces TSRdetector, a method to analyze differential usage of gene transcription start regions across tissues, cell types, and diseases, revealing unique transcriptional regulation patterns.

The paper identifies high-resolution eQTLs in kidney tissues using Bayesian fine mapping with integrative priors, improving resolution and functional relevance.

The paper develops RENIN, a regularized regression method, to predict gene regulatory networks from single nucleus multiomic data and applies it to identify regulators of failed kidney injury response.

The paper introduces gkmQC, a sequence-based model to assess and refine chromatin accessibility data quality, improving peak calling and regulatory element alignment.

This study uses single-cell multiomic analysis to define cellular complexity in ADPKD, identifying novel transcriptomic and epigenomic features in cystic kidney cells.

This study uses multimodal single-cell sequencing to show that chromatin accessibility and genetic background influence diabetic kidney disease progression through cell-specific mechanisms.

This study integrates snATAC-seq and snRNA-seq data to redefine cellular heterogeneity in the adult human kidney by identifying functional differences in chromatin accessibility and gene expression.

The paper uses single nucleus RNA sequencing to identify a proinflammatory and profibrotic proximal tubule cell state in mouse AKI that fails to repair, suggesting it as a therapeutic target.

This study uses snRNAseq to analyze early diabetic nephropathy in human kidneys, identifying gene expression changes in potassium secretion and angiogenic signaling across multiple cell types.