Jinzhuo Wang

This paper introduces MetaKG, a metabolite-centric knowledge graph with self-supervised learning that improves representation learning and uncovers biochemical relationships.

The paper introduces MorphAgent, a biologically grounded AI framework for cell profiling across microscopy modalities, improving feature design and performance in drug screening and disease analysis.

IDEAL-Age is a deep learning framework that profiles immunological aging at single-cell resolution, showing improved predictive performance and revealing cellular contributions to aging processes.

CellProphet infers dynamic gene regulatory networks using AI, outperforming existing methods in differentiation datasets and accurately predicting cell fate transitions in mouse models.