Jiangguo Zhang

This paper uses deep learning to quantify dynamic self-organization in Myxococcus xanthus by encoding microscopy images into interpretable features that predict developmental phenotypes.

This study challenges the traffic jam model of Myxococcus xanthus aggregation by showing streams are not essential for aggregate formation but may accelerate it, with a genetic component to streaming.

This study identifies a dual regulatory mechanism and substrate limitations that balance quinone synthesis benefits and toxicity in Lactococcus lactis.

The paper develops a deep-learning model to convert phase-contrast images into fluorescence-like images for better analysis of bacterial aggregation and rippling behaviors in Myxococcus xanthus.