Di Zhang

The paper develops a co-evolution algorithm to predict bacterial iron interaction networks based on siderophore synthetase-receptor gene pairs across Pseudomonas genomes, revealing habitat- and pathogen-specific interactions.

The paper develops a bioinformatic pipeline to predict bacterial siderophore structures and receptors from genome sequences, revealing significant diversity in pyoverdines and their receptors.

This study constructs a logic-incorporated gene regulatory network model to analyze how regulatory logic and noise influence cell fate decisions in differentiation and reprogramming.