William V. Trim

This paper introduces NORIGAMI, a multi-omics pipeline that combines imaging and deep learning to analyze kidney aging, revealing age-related structural and molecular changes.

This paper introduces a computational pipeline combining image processing and machine learning to segment and quantify kidney tissue structures using Normalized Raman Imaging, achieving high segmentation performance.

This paper introduces NoRI, a Raman imaging technique that enables quantitative, label-free analysis of kidney tissue, revealing sex-specific differences and dynamic changes in acute kidney injury.

This study identifies SREBP2 as a direct APC-AXIN1 substrate degraded via a β-catenin-independent pathway, regulating cholesterol metabolism and providing a target for APC-mutant colorectal cancer.