Yan Liu

Self-iterative multiple instance learning enables the prediction of CD4+ T cell immunogenic epitopes

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

MKFGO: Integrating Multi-Source Knowledge Fusion with Pre-Trained Language Model for High-Accuracy Protein Function Prediction

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

Supervised contrastive learning enhances MHC-II peptide binding affinity prediction

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: a Siamese network-based pipeline for the annotation of cell types using imperfect single-cell RNA-seq reference data

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

TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for High-Accuracy Gene Function Annotations

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

RFRSN: Improving protein fold recognition by siamese network

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