7 citations · 12 across the 6 of their papers we have counts for
6 papers
MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction
Cheng Tan, Zhenxiao Cao, Zhangyang Gao +6
Post-translational modifications (PTMs) profoundly expand the complexity and functionality of the proteome, regulating protein attributes and interactions that are crucial for biol…
Advances of Deep Learning in Protein Science: A Comprehensive Survey
Bozhen Hu, Cheng Tan, Lirong Wu +7
Protein representation learning plays a crucial role in understanding the structure and function of proteins, which are essential biomolecules involved in various biological proces…
PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction
Lirong Wu, Yufei Huang, Cheng Tan +5
Compound-Protein Interaction (CPI) prediction aims to predict the pattern and strength of compound-protein interactions for rational drug discovery. Existing deep learning-based me…
Deep Manifold Transformation for Protein Representation Learning
Bozhen Hu, Zelin Zang, Cheng Tan +1
Protein representation learning is critical in various tasks in biology, such as drug design and protein structure or function prediction, which has primarily benefited from protei…
Deep Manifold Graph Auto-Encoder for Attributed Graph Embedding
Bozhen Hu, Zelin Zang, Jun Xia +3
Representing graph data in a low-dimensional space for subsequent tasks is the purpose of attributed graph embedding. Most existing neural network approaches learn latent represent…
Segment Anything in Defect Detection
Bozhen Hu, Bin Gao, Cheng Tan +2
Defect detection plays a crucial role in infrared non-destructive testing systems, offering non-contact, safe, and efficient inspection capabilities. However, challenges such as lo…