龙亚辉｜中南大学｜学者主页

2026

DualBind: Dual-module protein-ligand binding affinity prediction with adaptive GNN and structure-aware transformer

Xuan Lin, Jinyu Zhou, Si-Qi Chen, Yahui Long, Zu-Guo Yu

Expert systems with applications

DOI

2025

scGANCL: Bidirectional Generative Adversarial Network for Imputing scRNA-Seq Data With Contrastive Learning

Wanwan Shi, Yahui Long, Jia-Wei Luo, Ying Liu, Zehao Xiong, Bo Wang, Zhongyuan Xu

IEEE Transactions on Computational Biology and Bioinformatics

DOI

2025

SAGAN: A Subgraph-Aware Graph Attention Network for Drug repositioning

Xiang-Mao Meng, Xinqiang Wen, Xinliang Sun, Ju Xiang, Yahui Long, Xuan Lin, Min Li

Tsinghua Science and Technology

DOI

2025

SpatialMap: A Scalable Deep Learning Method for Cell Typing in Subcellular Spatial Transcriptomics

Pengzhen Jia, Yahui Long, Yichao Zhao, Ning Zhang, Zhao-Yu Fang, Siqi Chen, Min Li

bioRxiv

DOI

2025

Language-Enhanced Representation Learning for Single-Cell Transcriptomics

Jiaqi Yang, Zhi-Yuan Liu, Yao-Rui Shi, Qing-Chuan Zhang, Chang-Sheng Nai, Jun-Feng Fang, Yahui Long, Yang Zhang, Xiang Wang

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2

DOI

2025

Predicting PROTAC-targeted Degradation and Designing Androgen Receptor Degraders with AiPROTAC

Li Zhang, Ren-Hong Sun, Xia Li, Chaowei Ren, Yahui Long, Wenjuan Tan, Xiaolong Wang, Ke Zou, Xiaobao Yang, Min Wu, Xiaoli Li, Xing Chen

bioRxiv

DOI

2025

Inferring spatial gene expression from tissue images using large-scale histology foundation model with SpaFoundation

Ning Zhang, Yahui Long, Si-Bo Xia, Pengzhen Jia, Yujie Jin, Siqi Chen, Jin-Miao Chen, Min Li

bioRxiv

DOI

2025

Incorporating multi-scale module kernel for disease-gene identification in biological networks

Ju Xiang, Kaixin Zeng, Shengkai Chen, Xiang-Mao Meng, Rui-Qing Zheng, Ying Zheng, Yahui Long, Min Li

bioRxiv

DOI

2025

stGNN: Spatially Informed Cell-Type Deconvolution Based on Deep Graph Learning and Statistical Modeling

Juntong Zhu, Dao-Yuan Wang, Siqi Chen, Lili Meng, Yahui Long, Cheng Liang

Interdisciplinary Sciences Computational Life Sciences

DOI

2025

High-Frequency-Aware Graph Integration for Subcellular Spatial Transcriptomics

Wanwan Shi, Bo Wang, Yahui Long, Ying Liu, Qiu Xiao, Yuting Bai, Xiaoyi Peng, Xiangtao Chen, Jia-Wei Luo

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2024

STCGAN: a novel cycle-consistent generative adversarial network for spatial transcriptomics cellular deconvolution

Bo Wang, Yahui Long, Yuting Bai, Jia-Wei Luo, Chee Keong Kwoh

Briefings Bioinform.

DOI

2023

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

Bo Wang, Jia-Wei Luo, Y. Liu, Wanwan Shi, Zehao Xiong, Cong Shen, Yahui Long

Briefings Bioinform.

DOI

2023

CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning

Bingxue Du, Yahui Long, Xiaoli Li, Min Wu, Jian-Yu Shi

Bioinform.

DOI

2023

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Yahui Long, Kok Siong Ang, Mengwei Li, K. Chong, R. Sethi, Chengwei Zhong, Hang Xu, Zhiwei Ong, K. Sachaphibulkij, Ao Chen, Li Zeng, H. Fu, Min Wu, Lina Hsiu Kim Lim, Long-Qi Liu, Jin-Miao Chen

bioRxiv

DOI

2023

Interpretable multi-view attention network for drug-drug interaction prediction

Xuan Lin, Qi Wen, Sijie Yang, Zu-Guo Yu, Yahui Long, Xiangxiang Zeng

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2023

Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks

Xuejing Shi, Juntong Zhu, Yahui Long, Cheng Liang

Briefings Bioinform.

DOI

2023

Integrated analysis of spatial multi-omics with SpatialGlue

Yahui Long, Kok Siong Ang, Sha Liao, R. Sethi, Heng Yang, Chengwei Zhong, Hang Xu, Nazihah Husna, Min Jian, L. Ng, Ao Chen, N. Gascoigne, Xun Xu, Jin-Miao Chen

bioRxiv

DOI

2022

Pre-training graph neural networks for link prediction in biomedical networks

Yahui Long, Min Wu, Yong Liu, Yuan Fang, C. Kwoh, Jin-Miao Chen, Jia-Wei Luo, Xiao-Li Li

Bioinform.

DOI

2022

DeepST: A versatile graph contrastive learning framework for spatially informed clustering, integration, and deconvolution of spatial transcriptomics

Yahui Long, Kok Siong Ang, Mengwei Li, K. Chong, R. Sethi, Chengwei Zhong, Hang Xu, Zhiwei Ong, K. Sachaphibulkij, Ao Chen, Zeng Li, H. Fu, Min Wu, Hsiu Kim Lina Lim, Long-Qi Liu, Jin-Miao Chen

2021

Class similarity network for coding and long non-coding RNA classification

Yu Zhang, Yahui Long, C. Kwoh

BMC Bioinformatics

DOI

2021

Graph Contextualized Attention Network for Predicting Synthetic Lethality in Human Cancers

Yahui Long, Min Wu, Yong Liu, Jie Zheng, C. Kwoh, Jia-Wei Luo, Xiaoli Li

bioRxiv

DOI

2021

Heterogeneous graph attention networks for drug virus association prediction

Yahui Long, Yu Zhang, Min Wu, Shaoliang Peng, C. Kwoh, Jia-Wei Luo, Xiao-Li Li

Methods

DOI

2020

Predicting human microbe-disease associations via graph attention networks with inductive matrix completion

Yahui Long, Jia-Wei Luo, Yu Zhang, Yan Xia

Briefings Bioinform.

DOI

2020

Predicting Human Microbe-Drug Associations via Graph Convolutional Network with Conditional Random Field

Yahui Long, Min Wu, C. Kwoh, Jia-Wei Luo, Xiaoli Li

Bioinform.

DOI

2020

Predicting Drugs for COVID-19/SARS-CoV-2 via Heterogeneous Graph Attention Networks

Yahui Long, Yu Zhang, Min Wu, Shaoliang Peng, C. Kwoh, Jia-Wei Luo, Xiaoli Li

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2020

DL-CRISPR: A Deep Learning Method for Off-Target Activity Prediction in CRISPR/Cas9 With Data Augmentation

Yu Zhang, Yahui Long, Rui Yin, C. Kwoh

IEEE Access

DOI

2020

NTSHMDA: Prediction of Human Microbe-Disease Association Based on Random Walk by Integrating Network Topological Similarity

Jia-Wei Luo, Yahui Long

IEEE/ACM Transactions on Computational Biology & Bioinformatics

DOI

2020

Ensembling graph attention networks for human microbe-drug association prediction

Yahui Long, Min Wu, Yong Liu, C. Kwoh, Jia-Wei Luo, Xiaoli Li

Bioinform.

DOI

2020

Deep learning based DNA:RNA triplex forming potential prediction

Yu Zhang, Yahui Long, C. Kwoh

BMC Bioinformatics

DOI

2020

Association Mining to Identify Microbe Drug Interactions Based on Heterogeneous Network Embedding Representation

Yahui Long, Jia-Wei Luo

IEEE journal of biomedical and health informatics

DOI

2019

WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network

Yahui Long, Jia-Wei Luo

BMC Bioinformatics

DOI

龙亚辉

精选作品

期刊论文

DualBind: Dual-module protein-ligand binding affinity prediction with adaptive GNN and structure-aware transformer

scGANCL: Bidirectional Generative Adversarial Network for Imputing scRNA-Seq Data With Contrastive Learning

SAGAN: A Subgraph-Aware Graph Attention Network for Drug repositioning

SpatialMap: A Scalable Deep Learning Method for Cell Typing in Subcellular Spatial Transcriptomics

Language-Enhanced Representation Learning for Single-Cell Transcriptomics

Predicting PROTAC-targeted Degradation and Designing Androgen Receptor Degraders with AiPROTAC

Inferring spatial gene expression from tissue images using large-scale histology foundation model with SpaFoundation

Incorporating multi-scale module kernel for disease-gene identification in biological networks

stGNN: Spatially Informed Cell-Type Deconvolution Based on Deep Graph Learning and Statistical Modeling

High-Frequency-Aware Graph Integration for Subcellular Spatial Transcriptomics

STCGAN: a novel cycle-consistent generative adversarial network for spatial transcriptomics cellular deconvolution

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism

CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Interpretable multi-view attention network for drug-drug interaction prediction

Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks

Integrated analysis of spatial multi-omics with SpatialGlue

Pre-training graph neural networks for link prediction in biomedical networks

DeepST: A versatile graph contrastive learning framework for spatially informed clustering, integration, and deconvolution of spatial transcriptomics

Class similarity network for coding and long non-coding RNA classification

Graph Contextualized Attention Network for Predicting Synthetic Lethality in Human Cancers

Heterogeneous graph attention networks for drug virus association prediction

Predicting human microbe-disease associations via graph attention networks with inductive matrix completion

Predicting Human Microbe-Drug Associations via Graph Convolutional Network with Conditional Random Field

Predicting Drugs for COVID-19/SARS-CoV-2 via Heterogeneous Graph Attention Networks

DL-CRISPR: A Deep Learning Method for Off-Target Activity Prediction in CRISPR/Cas9 With Data Augmentation

NTSHMDA: Prediction of Human Microbe-Disease Association Based on Random Walk by Integrating Network Topological Similarity

Ensembling graph attention networks for human microbe-drug association prediction

Deep learning based DNA:RNA triplex forming potential prediction

Association Mining to Identify Microbe Drug Interactions Based on Heterogeneous Network Embedding Representation

WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network

研究方向