activity
20202025
most citedMulti-branch Attentive Transformer

15 citations · 41 across the 12 of their papers we have counts for

collaborators

8 papers

cs.AI2025

MolChord: Structure-Sequence Alignment for Protein-Guided Drug Design

Wei Zhang, Zekun Guo, Yingce Xia +4

Structure-based drug design (SBDD), which maps target proteins to candidate molecular ligands, is a fundamental task in drug discovery. Effectively aligning protein structural repr…

q-bio.QM20241 cited

SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation

Liang He, Peiran Jin, Yaosen Min +7

Proteins, essential to biological systems, perform functions intricately linked to their three-dimensional structures. Understanding the relationship between protein structures and…

q-bio.BM20222 cited

Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-design

Kaiyuan Gao, Lijun Wu, Jinhua Zhu +8

Antibodies are versatile proteins that can bind to pathogens and provide effective protection for human body. Recently, deep learning-based computational antibody design has attrac…

cs.CL2021

Discovering Drug-Target Interaction Knowledge from Biomedical Literature

Yutai Hou, Yingce Xia, Lijun Wu +6

The Interaction between Drugs and Targets (DTI) in human body plays a crucial role in biomedical science and applications. As millions of papers come out every year in the biomedic…

cs.CL20211 cited

UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost

Zhen Wu, Lijun Wu, Qi Meng +5

Transformer architecture achieves great success in abundant natural language processing tasks. The over-parameterization of the Transformer model has motivated plenty of works to a…

cs.CL20213 cited

IOT: Instance-wise Layer Reordering for Transformer Structures

Jinhua Zhu, Lijun Wu, Yingce Xia +5

With sequentially stacked self-attention, (optional) encoder-decoder attention, and feed-forward layers, Transformer achieves big success in natural language processing (NLP), and…