5 citations · 13 across the 15 of their papers we have counts for
6 papers · 1 filter
Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language Model
Yang Tan, Ruilin Wang, Banghao Wu +2
Enzyme engineering enables the modification of wild-type proteins to meet industrial and research demands by enhancing catalytic activity, stability, binding affinities, and other…
Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection
Song Li, Yang Tan, Song Ke +2
Immunogenicity prediction is a central topic in reverse vaccinology for finding candidate vaccines that can trigger protective immune responses. Existing approaches typically rely…
Secondary Structure-Guided Novel Protein Sequence Generation with Latent Graph Diffusion
Yutong Hu, Yang Tan, Andi Han +3
The advent of deep learning has introduced efficient approaches for de novo protein sequence design, significantly improving success rates and reducing development costs compared t…
Protein Representation Learning with Sequence Information Embedding: Does it Always Lead to a Better Performance?
Yang Tan, Lirong Zheng, Bozitao Zhong +2
Deep learning has become a crucial tool in studying proteins. While the significance of modeling protein structure has been discussed extensively in the literature, amino acid type…
ProtSolM: Protein Solubility Prediction with Multi-modal Features
Yang Tan, Jia Zheng, Liang Hong +1
Understanding protein solubility is essential for their functional applications. Computational methods for predicting protein solubility are crucial for reducing experimental costs…
Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models
Yang Tan, Mingchen Li, Bingxin Zhou +7
Fine-tuning Pre-trained protein language models (PLMs) has emerged as a prominent strategy for enhancing downstream prediction tasks, often outperforming traditional supervised lea…