Yan Liu

ImmuScope predicts CD4+ T cell immunogenic epitopes using self-iterative multiple-instance learning, improving accuracy with multi-allelic and single-allelic data.

MKFGO integrates multi-source biological data with deep learning to predict protein functions, outperforming existing methods on 1522 proteins.

This paper introduces ConBoTNet, a deep learning model that improves MHC-II peptide binding affinity prediction using supervised contrastive learning and bottleneck transformers, achieving better performance than existing methods.

scRCA improves cell type annotation using noisy reference data by combining a Siamese network with noise-robust loss functions and outperforms existing methods.

TripletGO improves gene function annotations by integrating transcript expression, sequence alignment, and probability models across multiple species and proteins.

This paper improves protein fold recognition by combining discriminative feature extraction with a siamese network to better measure similarity between protein sequences.