3 citations · 6 across the 4 of their papers we have counts for
5 papers
MP2D: Constrained Monte Carlo Tree-Guided Diffusion for Multi-Objective Protein Sequence Design
Zitai Kong, Yifan Dong, Yixuan Wu +3
Designing functional protein sequences that satisfy multiple desired properties is a core research focus of protein engineering. Prior methods struggle with inability or inefficien…
ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings
Zitai Kong, Yiheng Zhu, Yinlong Xu +7
The design of protein sequences with desired functionalities is a fundamental task in protein engineering. Deep generative methods, such as autoregressive models and diffusion mode…
SALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning
Mingze Yin, Hanjing Zhou, Jialu Wu +8
Antibodies safeguard our health through their precise and potent binding to specific antigens, demonstrating promising therapeutic efficacy in the treatment of numerous diseases, i…
MambaCapsule: Towards Transparent Cardiac Disease Diagnosis with Electrocardiography Using Mamba Capsule Network
Yinlong Xu, Zitai Kong, Yixuan Wu +5
Cardiac arrhythmia, a condition characterized by irregular heartbeats, often serves as an early indication of various heart ailments. With the advent of deep learning, numerous inn…
Generative AI for Controllable Protein Sequence Design: A Survey
Yiheng Zhu, Zitai Kong, Jialu Wu +6
The design of novel protein sequences with targeted functionalities underpins a central theme in protein engineering, impacting diverse fields such as drug discovery and enzymatic…