Thao Vu

This study uses 3D lung models to show that environmental stiffness has the strongest effect on fibroblast phenotype and that both matrix composition and stiffness influence gene expression in fibrotic disease.

cytoKernel assesses differential expression in single-cell data by using kernel embeddings to detect both aggregate and subtle variations, outperforming existing methods.

The paper identifies proteomic networks and genetic variants associated with smoking and COPD phenotypes using multi-ethnic proteomic data and network-based GWAS.

SmCCNet 2.0 integrates multi-omics data with a phenotype to reconstruct networks specific to that phenotype, offering improved setup flexibility and user experience.

SpaceANOVA analyzes spatial co-occurrence of cell types in multiplex imaging data across tissue or disease groups using point process and functional ANOVA, revealing novel insights in colorectal cancer precursor lesions.

The paper introduces FunSpace, a method using spatial entropy and functional principal component analysis to assess spatial heterogeneity in tumor microenvironments and its impact on survival.

The paper introduces a spatial and functional analytic approach to model the impact of tumor-stromal cell interactions on survival in cancer patients using imaging data.

DenVar analyzes multiplex imaging data to assess associations between functional marker densities and clinical outcomes without thresholding.