Tian Cai

Deciphering Phage-Host Specificity Based on the Association of Phage Depolymerases and Bacterial Surface Glycan with Deep Learning

The paper develops SpikeHunter, a deep learning model to identify tailspike proteins from prophages, revealing associations between these proteins and bacterial serotypes.

Binding Site-enhanced Sequence Pretraining and Out-of-cluster Meta-learning Predict Genome-Wide Chemical-Protein Interactions for Dark Proteins

PortalCG predicts chemical-protein interactions for dark proteins using a deep learning framework that integrates binding site information and meta-learning, outperforming existing methods in out-of-distribution scenarios.

DeepREAL: A Deep Learning Powered Multi-scale Modeling Framework Towards Predicting Out-of-distribution Receptor Activity of Ligand Binding

DeepREAL predicts genome-scale receptor activity of ligand binding for novel chemicals using deep learning, addressing data scarcity and distribution shifts.

A deep learning framework for elucidating whole-genome chemical interaction space

This paper introduces DISAE, a deep learning framework that predicts ligands for unannotated proteins and applies it to assign ligands to human orphan GPCRs.

Genome-wide Prediction of Small Molecule Binding to Remote Orphan Proteins Using Distilled Sequence Alignment Embedding

This paper introduces DISAE, a protein pre-training method for deorphanization, which improves generalizability and outperforms existing methods in predicting small molecule binding to orphan proteins.