Liwen Xu

This paper introduces HomoDSP, a method for DNA-binding specificity prediction using homologous protein-DNA structures, showing improved accuracy and generalization over existing methods.

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 ESM-DBP, a domain-adapted protein language model for DNA-binding proteins, showing improved prediction performance and interpretability.

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.