Yuchuan Wang

This paper introduces U-Pert, a framework for modeling unbalanced perturbation dynamics in single-cell data, enabling forward prediction and inverse design of cellular interventions.

The paper integrates 4D Nucleome data to analyze 3D genome structure and function in human cells, revealing chromatin domains, loops, and interactions, and showing how genetic variants affect genome folding.

The paper examines genome organization in human cells relative to nuclear locales, finding that gene expression and replication timing correlate with different nuclear structures and that LADs and iLADs compete for lamina attachment.

This study investigates how chromatin-associated RNA interacts with 3D genome organization in human cells, revealing a feedback loop between RNA distribution and chromatin structure.

Nucleome Browser integrates heterogeneous 4D Nucleome data into an interactive platform for visualization and exploration across biological contexts.

The paper introduces a machine learning method to predict DNA replication timing from sequence features and identifies genome-wide sequence elements that modulate replication timing.

The paper introduces SPIN, a method to identify genome-wide nuclear spatial localization patterns by integrating nuclear compartment mapping and chromatin interaction data.

The paper introduces TSA-Seq, a method to measure chromosomal distances to nuclear structures and reveals a spatial gradient in genome activity correlated with nuclear compartments.

This study identifies sequence-based features that predict CTCF-mediated chromatin loops using a machine learning model called CTCF-MP.