Yejun Wang

HPInet predicts host-pathogen protein-protein interactions using a transformer-based model, achieving high accuracy and identifying key residues from sequence data.

The paper uses CRISPRi-seq to identify FprB as a synergistic target for gallium therapy in Pseudomonas aeruginosa, enhancing gallium's efficacy against infections.

The paper identifies 21 OMP families in E. coli showing mosaic evolution, including 16 new families, and links their variable regions to immunogenicity and antigenicity.

This paper introduces T6CNN, a model that improves T6SE prediction by integrating signal sequences, evolutionary data, and pre-trained features, achieving higher accuracy, sensitivity, and specificity than existing tools.

This study reconstructs ancient Salmonella chromosomes and shows genetic rearrangements affect gene expression and chromosomal conformation across lineages.

T4SEpp predicts bacterial type IV secreted effectors using protein language models and integrates multiple modules, achieving high sensitivity and specificity.

The paper introduces a recursive Hidden Markov Model profile-alignment strategy to identify new bacterial type III secreted effectors, finding 155 effectors and 59 proteins with N-terminal signal sequences across 27 genera.