22 citations · 68 across the 15 of their papers we have counts for
16 papers
CovDocker: Benchmarking Covalent Drug Design with Tasks, Datasets, and Solutions
Yangzhe Peng, Kaiyuan Gao, Liang He +4
Molecular docking plays a crucial role in predicting the binding mode of ligands to target proteins, and covalent interactions, which involve the formation of a covalent bond betwe…
UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials
Gongbo Zhang, Yanting Li, Renqian Luo +31
Function in natural systems arises from one-dimensional sequences forming three-dimensional structures with specific properties. However, current generative models suffer from crit…
Fast and Accurate Blind Flexible Docking
Zizhuo Zhang, Lijun Wu, Kaiyuan Gao +3
Molecular docking that predicts the bound structures of small molecules (ligands) to their protein targets, plays a vital role in drug discovery. However, existing docking methods…
Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
Yingce Xia, Peiran Jin, Shufang Xie +43
Foundation models have revolutionized natural language processing and artificial intelligence, significantly enhancing how machines comprehend and generate human languages. Inspire…
Tokenizing 3D Molecule Structure with Quantized Spherical Coordinates
Kaiyuan Gao, Yusong Wang, Haoxiang Guan +5
The application of language models (LMs) to molecular structure generation using line notations such as SMILES and SELFIES has been well-established in the field of cheminformatics…
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…
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling
Qizhi Pei, Rui Yan, Kaiyuan Gao +2
The integration of molecular and natural language representations has emerged as a focal point in molecular science, with recent advancements in Language Models (LMs) demonstrating…
FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation
Kaiyuan Gao, Qizhi Pei, Gongbo Zhang +3
Molecular docking is a pivotal process in drug discovery. While traditional techniques rely on extensive sampling and simulation governed by physical principles, these methods are…
Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey
Qizhi Pei, Zhimeng Zhou, Kaiyuan Gao +6
The integration of biomolecular modeling with natural language (BL) has emerged as a promising interdisciplinary area at the intersection of artificial intelligence, chemistry and…
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
Qizhi Pei, Lijun Wu, Kaiyuan Gao +6
Recent research trends in computational biology have increasingly focused on integrating text and bio-entity modeling, especially in the context of molecules and proteins. However,…
BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations
Qizhi Pei, Wei Zhang, Jinhua Zhu +5
Recent advancements in biological research leverage the integration of molecules, proteins, and natural language to enhance drug discovery. However, current models exhibit several…
FABind: Fast and Accurate Protein-Ligand Binding
Qizhi Pei, Kaiyuan Gao, Lijun Wu +7
Modeling the interaction between proteins and ligands and accurately predicting their binding structures is a critical yet challenging task in drug discovery. Recent advancements i…
Examining User-Friendly and Open-Sourced Large GPT Models: A Survey on Language, Multimodal, and Scientific GPT Models
Kaiyuan Gao, Sunan He, Zhenyu He +4
Generative pre-trained transformer (GPT) models have revolutionized the field of natural language processing (NLP) with remarkable performance in various tasks and also extend thei…
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…
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
Jinsong Chen, Kaiyuan Gao, Gaichao Li +1
The graph Transformer emerges as a new architecture and has shown superior performance on various graph mining tasks. In this work, we observe that existing graph Transformers trea…
Revisiting Language Encoding in Learning Multilingual Representations
Shengjie Luo, Kaiyuan Gao, Shuxin Zheng +4
Transformer has demonstrated its great power to learn contextual word representations for multiple languages in a single model. To process multilingual sentences in the model, a le…