Shuxiong Wang

This study uses single-cell RNA sequencing to compare human skin equivalent organoids with in vivo epidermis, identifying both similarities and unique features in their cellular states and differentiation trajectories.

MuTrans identifies transition cells and quantifies cell-state transitions using multiscale stochastic dynamics, applied to diverse single-cell datasets.

The paper uses single-cell RNA sequencing to identify spatially distinct basal stem cell populations in human epidermis and shows their role in maintaining epidermal homeostasis through signaling and differentiation.

This paper introduces SoptSC, a method that integrates clustering, lineage inference, and communication network prediction in single-cell transcriptomics using a similarity matrix optimization framework.