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20212026
most citedFeature screening for clustering analysis

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2026

Distribution-free screening of spatially variable genes in spatial transcriptomics

Changhu Wang, Qiyun Huang, Zihao Chen +2

Spatial transcriptomics (ST) technologies enable transcriptome-wide gene expression profiling while preserving spatial resolution, offering unprecedented opportunities to uncover c…

stat.ME2023★ 2 cited

Feature screening for clustering analysis

Changhu Wang, Zihao Chen, Ruibin Xi

In this paper, we consider feature screening for ultrahigh dimensional clustering analyses. Based on the observation that the marginal distribution of any given feature is a mixtur…

stat.ME2022

Network Analysis of Count Data from Mixed Populations

Junjie Tang, Changhu Wang, Feiyi Xiao +1

In applications such as gene regulatory network analysis based on single-cell RNA sequencing data, samples often come from a mixture of different populations and each population ha…

q-bio.MN2022

Single-cell gene regulatory network analysis for mixed cell populations with applications to COVID-19 single cell data

Junjie Tang, Changhu Wang, Feiyi Xiao +1

Gene regulatory network (GRN) refers to the complex network formed by regulatory interactions between genes in living cells. In this paper, we consider inferring GRNs in single cel…

stat.ME2021

Gene regulatory network in single cells based on the Poisson log-normal model

Feiyi Xiao, Junjie Tang, Huaying Fang +1

Gene regulatory network inference is crucial for understanding the complex molecular interactions in various genetic and environmental conditions. The rapid development of single-c…