Tian Hong

EMTscore provides an efficient tool for unbiased scoring of EMT pathways in single-cell or bulk omics data and enables rapid screening of gene set correlations.

This study identifies 3D genome compartment changes associated with epithelial-mesenchymal transition and organotropism in breast cancer metastasis.

The paper investigates how intercellular signaling influences phenotypic transitions in cancer cells using scRNA-seq data and mathematical models, finding that signaling reinforces heterogeneity and robustness in tumor populations.

This paper develops a reaction-diffusion model to explain the spatial control of gene silencing during X chromosome inactivation, showing how feedback loops and chromatin modifications regulate the spread of silencing.

EssSubgraph improves essential gene prediction by integrating networks and omics data, showing better performance and cross-species generalizability than existing methods.

The paper identifies age-dependent changes in MECP2 expression and associated behavioral and cellular phenotypes in a female mouse model of Rett syndrome.

This study shows that cooperative RNA degradation via microRNA binding sites can stabilize intermediate EMT states without transcriptional feedback, supporting a phenotypic continuum in EMT.

The paper compares dose- and time-dependent EMT transcriptomes to show stable intermediate states and improved gene detection in dose-dependent experiments.

The paper shows that regulated RNA degradation can generate oscillations and restore multimodal gene expression in progenitor cells without requiring feedback loops.

This study introduces gsPCA and gsNMF for analyzing transcriptome data, showing they provide interpretable, transferrable, and gene-specific functional insights comparable to existing methods.

The paper develops a mathematical model to explain how eS6 phosphorylation integrates circadian and diel signals to detect daylength changes.

The paper uses combinatorial perturbations to study EMT gene regulation, finding that mesenchymal genes show diverse dependencies on TGF-β and ZEB1, with functional differences in motility and cancer survival.

The paper identifies a network motif family that enables multistep cell fate transitions with restricted reversibility, validated in T cell development.