Weikang Wang

The paper introduces SCIM, a method using information geometry to quantify cell phenotype transition manifolds by analyzing curvature and velocity in single-cell gene expression data.

The paper analyzes single-cell dynamics during state transitions, finding that cell states are sensitive to few 'stiff' parameters and robust to many 'sloppy' parameters, suggesting a principle of least action.

LivecellX corrects segmentation and tracking errors in live-cell imaging using deep learning and provides tools for lineage reconstruction and dynamic analysis.

The paper analyzes single-cell RNA sequencing data using transition path theory to study gene regulation during cell phenotypic transitions, finding increased intercommunity regulation and GRN frustration.

The paper develops a live-cell imaging platform to study phenotypic transitions, revealing dynamics missed by snapshot data.

This paper develops a modular Gibson assembly method for efficient and cost-effective CRISPR donor DNA construct generation, showing improved assembly efficiency compared to conventional methods.

The paper shows that TGF-β signaling duration is interpreted through pathway crosstalk that controls SNAIL1 expression.