3 papers
stat.ME2026
Supervised Bayesian joint graphical model for simultaneous network estimation and subgroup identification
Xing Qin, Xu Liu, Shuangge Ma +1
Heterogeneity is a fundamental characteristic of cancer. To accommodate heterogeneity, subgroup identification has been extensively studied and broadly categorized into unsupervise…
stat.AP2026
Heterogeneous gene network estimation for single-cell transcriptomic data via a joint regularized deep neural network
Jingyuan Yang, Tao Li, Tianyi Wang +2
Estimation of intracellular gene networks has been a critical component of single-cell transcriptomic data analysis, which can provide crucial insights into the complex interplay b…
stat.AP2025
A flexible Bayesian framework for detecting cross-sample spatial expression variability in heterogeneous tissues
Meng Zhou, Shuangge Ma, Mengyun Wu
Spatial transcriptomics measures gene expression alongside the spatial coordinates of each capture spot or cell across tissue samples. The detection of spatially variable (SV) gene…