Xiao-Yong Pan

ProRB: a structure-free unified framework for joint prediction and design of protein–RNA interactions

ProRB is introduced, a unified sequence-based framework that jointly estimates protein–RNA binding affinity, predicts binding interfaces in proteins and RNAs, and generates protein-binding RNA sequences from protein sequences that provides a scalable unified model for decoding the protein–RNA interaction and engineerin...

Structure-alignment-driven cross-graph modeling for functional RNA design

Subcellularly Resolved Single-Cell Embedding Learning with Transcriptomic data, Protein Structure and Localization Information

This work proposes a multimodal framework for learning subcellularly resolved cell embeddings by jointly leveraging RNA expression profiles, protein sequence representations, and protein structural information, and is the first framework that produces subcellularly resolved cell embeddings by jointly incorporating tran...

Benchmarking protein sequence and structure search methods for remote homology detection.

This benchmark establishes a standardized framework for evaluating protein similarity search methods, providing a practical resource for method selection and a foundation for the development of next-generation approaches capable of addressing diverse homology search challenges.

IgGM2: An All-Atom Foundation Model for Adaptive Immune Receptor Design

IgGM2 follows a structure-to-design strategy: it first learns how immune receptors are positioned around fixed target structures, and then transfers this target-conditioned structural prior to CDR design, allowing frame-work geometry to adapt to designed CDRs without separate inverse folding or external sidechain packi...