Boya Ji

CAPTAIN is a multimodal foundation model trained on single-cell RNA and protein data, improving multi-omics integration and uncovering protein-driven intercellular dynamics.

GeSite identifies nucleic acid-binding residues using a domain-adaptive protein language model and explainable geometric deep learning, showing superior performance on benchmark datasets.

SpaCCC uses a fine-tuned LLM and gene network to infer cell-cell communications from spatial transcriptomic data, outperforming existing methods and revealing hidden ligand-receptor pairs.

This paper introduces scDCA, a method to identify dominant cell communication assemblies from scRNA-seq data, validated in renal cell carcinoma to reveal key immune gene expression patterns and therapeutic responses.

HyperVR predicts virulence factors and antibiotic resistance genes in microbial data using gene sequences, achieving high precision and recall without strict thresholds.