1 citations · 1 across the 9 of their papers we have counts for
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Structure Learning on Clustered Data
Ryan Thompson, Matt P. Wand, Veerabhadran Baladandayuthapani
Recent algorithmic advances have made directed acyclic graph (DAG) structure learning scalable for causal discovery. Yet, the currently available techniques assume a completely hom…
MoSAIC: Multi-Resolution Spatial Regression Analysis of Cellular Colocalizations in Cancer Imaging
Jessica Aldous, Michele Peruzzi, Maria Masotti +4
Hierarchical multiplex imaging approaches generate spatially resolved single-cell measurements across multiple, spatially organized fields of view (FOVs) within patient tumor speci…
Multi-resolution Spatial Graphical Regression Models for Hierarchical Spatial Transcriptomics Data
Liying Chen, Satwik Acharyya, Allison M. May +3
Advances in spatial transcriptomics (ST) technologies enable systematic molecular characterization of tumor microenvironment, tumor gradients and gene regulatory networks. Cancer p…
A Time-Varying and Covariate-Dependent Correlation Model for Multivariate Longitudinal Studies
Qingzhi Liu, Gen Li, Anastasia K. Yocum +3
In multivariate longitudinal studies, associations between outcomes often exhibit time-varying and individual level heterogeneity, motivating the modeling of correlations as an exp…