Ruolin He

The paper introduces CIM, a method to predict CFM-Rec interactions from genomic data, revealing topological patterns in microbial communities.

The paper constructs a global metagenomic atlas of extremophilic microbes, revealing habitat-specific biosynthetic potential linked to adaptation in extreme environments.

Random forest predictors PARAS and PARASECT, trained on 3,653 curated adenylation domains, outperform earlier NRPS substrate predictors and correctly assigned L-Trp to an unusual tryptopeptin synthetase domain.

This paper introduces a genome-based pipeline to predict pyoverdine structures and their receptors in Pseudomonas using pHMMs and co-evolutionary analysis, validated across 14,230 genomes.

The paper develops a framework to trace siderophore biosynthesis to primary metabolism and applies it to identify metabolic differences between beneficial and pathogenic bacteria.

The paper develops a functional-space framework to analyze siderophore biosynthesis across bacteria, revealing ecological drivers over phylogenetic constraints.

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.

SIDERITE identifies new iron-binding molecules by analyzing chemical structures and confirming their iron-binding ability through experimental validation.

The paper introduces a standardized NRPS architecture using conserved motifs, leading to new subtype classifications, novel motifs, and insights into reengineering challenges.