Zhenyi Zhang

CytoBridge reconstructs continuous virtual cell dynamics from sparse spatial transcriptomic data across development, regeneration, and neurodegeneration.

CellCompass, an agentic AI system, models cell dynamics from single-cell measurements and improves predictions by integrating new biological constraints and experimental data.

MOFI reconstructs continuous cell fate transitions from paired multi-omics snapshots across time, revealing coordinated changes in transcriptomic, chromatin, and protein layers.

PhyloFM reconstructs continuous cell-fate dynamics using lineage constraints from single-cell data, improving accuracy in multiple biological systems.

GeoBridge transforms sparse scRNA-seq data into a continuous landscape for reconstructing and navigating cellular state transitions.

This study benchmarks zero-shot single-cell foundation model embeddings for cellular dynamics reconstruction and finds they underperform a traditional HVG baseline in capturing complex temporal patterns.

This paper introduces DECENT, a deep learning method to reconstruct embryonic copy number variations and reduce maternal DNA contamination in cfDNA from SECM, improving the accuracy of noninvasive preimplantation genetic testing.