章天骄｜东北林业大学｜学者主页

2026

CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images

Tianjiao Zhang, Long Wan, Hongfei Zhang, Zhongqian Zhao, Haijie Cui, Jianli Ma

Briefings Bioinform.

DOI

2026

MOTCS: A Cancer Subtype Classification and Key Biomarker Recognition Model Based on Multi-Omics Data Integration of Transformer

Ping Meng, Guo-Hua Wang, Tianjiao Zhang

International Journal of Molecular Sciences

DOI

2026

GMHAN: a heterogeneous graph attention framework for prioritizing coding and non-coding driver genes

Ping Meng, Tianjiao Zhang, Guohua Wang

Bioinform.

DOI

2026

spAttClu: a spatial domain clustering model leveraging spatially weighted graph attention and contrastive learning

Tianjiao Zhang, Ruolan Zhang, Hongfei Zhang, Zhongqian Zhao, Ruihan Wang, Sheng-He Li, Yucai Jiang, Binyang Wei, Guohua Wang

Bioinform.

DOI

2026

SINTER3D: continuous 3D reconstruction of spatial transcriptomics via implicit neural representations

Tianjiao Zhang, Sheng-He Li, Hongfei Zhang, Ruolan Zhang, Zhongqian Zhao, Ruihan Wang, Xiao-Peng Teng, Long Wan, Yucai Jiang, Jianyi Lyu, Run-Qing Wang, Guo-Hua Wang

Genome Biology

DOI

2025

CellGAT: A GAT-Based Method for Constructing a Cell Communication Network Integrating Multiomics Information

Tianjiao Zhang, Zhenao Wu, Liang-Yu Li, Ji-Xiang Ren, Zi-Heng Zhang, Jingyu Zhang, Guo-Hua Wang

Biomolecules

DOI

2025

IMAGO: An Improved Model Based on Attention Mechanism for Enhanced Protein Function Prediction

Meiling Liu, Longchang Liang, Qiu-Tong Wang, Yun-Meng Zhang, Lin Shi, Tianjiao Zhang, Zhen-Xing Wang

Biomolecules

DOI

2025

spaMGCN: a graph convolutional network with autoencoder for spatial domain identification using multi-scale adaptation

Tianjiao Zhang, Hongfei Zhang, Zhongqian Zhao, Saihong Shao, Yucai Jiang, Xiang Zhang, Guo-Hua Wang

Genome Biology

DOI

2025

KansformerEPI: a deep learning framework integrating KAN and transformer for predicting enhancer–promoter interactions

Tianjiao Zhang, Saihong Shao, Hongfei Zhang, Zhongqian Zhao, Xingjie Zhao, Xiang Zhang, Zhenxing Wang, Guo-Hua Wang

Briefings Bioinform.

DOI

2025

SGCD: High‐Resolution Spatial Domain Characterization via Data Interpolation and Cell‐Type Deconvolution

Tianjiao Zhang, Sheng-He Li, Ruo-Lan Zhang, Hongfei Zhang, Zhongqian Zhao, Hao Sun, Zhenao Wu, Guo-Hua Wang

Advancement of science

DOI

2025

CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data

Chonghui Liu, Murong Zhou, Zhidong Wang, Chen Yang, Yan Zhang, Zhong-Jun Jiang, Yu-Hang Yin, Zeyu Luo, Tianjiao Zhang, Guo-Hua Wang, Lei Yuan

bioRxiv

DOI

2025

Multi-omics single-cell data alignment and integration with enhanced contrastive learning and differential attention mechanism

Tianjiao Zhang, Zhongqian Zhao, Hongfei Zhang, Zhenao Wu, Fang Wang, Guo-Hua Wang

Bioinform.

DOI

2025

Library size-stabilized metacells construction enhances co-expression network analysis in single-cell data

Tianjiao Zhang, Haibin Zhu

PLoS Comput. Biol.

DOI

2024

scDRMAE: integrating masked autoencoder with residual attention networks to leverage omics feature dependencies for accurate cell clustering

Tianjiao Zhang, Hongfei Zhang, Ji-Xiang Ren, Zhenao Wu, Zhongqian Zhao, Guo-Hua Wang

Bioinform.

DOI

2024

scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering

Tianjiao Zhang, Ji-Xiang Ren, Liang-Yu Li, Zhenao Wu, Zi-Heng Zhang, Guanghui Dong, Guo-Hua Wang

International Journal of Molecular Sciences

DOI

2024

SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model

Ben-Zhi Dong, Zheng Liu, Da-Li Xu, Chang Hou, Guanghui Dong, Tianjiao Zhang, Guo-Hua Wang

Computational and Structural Biotechnology Journal

DOI

2024

Utilizing Deep Neural Networks to Fill Gaps in Small Genomes

Yu Chen, Gang Wang, Tianjiao Zhang

International Journal of Molecular Sciences

DOI

2024

cfDiffusion: diffusion-based efficient generation of high quality scRNA-seq data with classifier-free guidance

Tianjiao Zhang, Zhongqian Zhao, Ji-Xiang Ren, Zi-Heng Zhang, Hongfei Zhang, Guo-Hua Wang

Briefings Bioinform.

DOI

2024

DrugReSC: targeting disease-critical cell subpopulations with single-cell transcriptomic data for drug repurposing in cancer

Chonghui Liu, Yan Zhang, Yingjian Liang, Tianjiao Zhang, Guohua Wang

Briefings Bioinform.

DOI

2024

scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data

Zhen-Ze Liu, Yingjian Liang, Guo-Hua Wang, Tianjiao Zhang

Briefings Bioinform.

DOI

2024

GAADE: identification spatially variable genes based on adaptive graph attention network

Tianjiao Zhang, Hao Sun, Zhenao Wu, Zhongqian Zhao, Xingjie Zhao, Hongfei Zhang, B. Gao, Guo-Hua Wang

Briefings Bioinform.

DOI

2024

VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell–cell communication network

Tianjiao Zhang, Xiang Zhang, Zhenao Wu, Ji-Xiang Ren, Zhongqian Zhao, Hongfei Zhang, Guo-Hua Wang, Tao Wang

Briefings Bioinform.

DOI

2024

GATv2EPI: Predicting Enhancer–Promoter Interactions with a Dynamic Graph Attention Network

Tianjiao Zhang, Xingjie Zhao, Hao Sun, B. Gao, Xiaoqi Liu

Genes

DOI

2024

CPPLS-MLP: a method for constructing cell–cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data

Tianjiao Zhang, Zhenao Wu, Liang-Yu Li, Ji-Xiang Ren, Zi-Heng Zhang, Guo-Hua Wang

Briefings Bioinform.

DOI

2024

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

Tianjiao Zhang, Zi-Heng Zhang, Liang-Yu Li, Ji-Xiang Ren, Zhenao Wu, B. Gao, Guo-Hua Wang

Biomolecules

DOI

2023

基于IRS辅助的MIMO车联网系统联合波束成形设计

张雷，王玉，田建杰，张琳，章天骄

《通信学报》

2023

MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding

Benzhi Dong, Wei-Dong Sun, Dali Xu, Guo-Hua Wang, Tianjiao Zhang

Comput. Biol. Medicine

DOI

2023

GTAD: a graph-based approach for cell spatial composition inference from integrated scRNA-seq and ST-seq data

Tianjiao Zhang, Zi-Heng Zhang, Liang-Yu Li, Benzhi Dong, Guo-Hua Wang, Dandan Zhang

Briefings Bioinform.

DOI

2023

DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA–Disease Association Prediction

Benzhi Dong, Wei-Dong Sun, Dali Xu, Guo-Hua Wang, Tianjiao Zhang

Biomolecules

DOI

2019

Ground resource optimization for navigation constellation based on satellite link scheduling

Tianjiao Zhang, Jing Li, Yikang Yang, Hengnian Li, Jisheng Li, Zexi Li

Engineering Optimization，Vol. 510, No. 4

DOI

2018

[Review] Metaheuristics for the tabu clustered traveling salesman problem

Tianjiao Zhang, Liangjun Ke, Jing Li, Jisheng Li, Jingqi Huang, Zexi Li

Computers & Operations Research，Vol. 89

DOI

2018

基于排队论的D2D蜂窝异构网络的性能分析

辛建芳，朱琦，梁广俊，章天骄

《信号处理》

2010

Prioritization of disease microRNAs through a human phenome-microRNAome network

Qinghua Jiang, Yangyang Hao, Guo-Hua Wang, Liran Juan, Tianjiao Zhang, Mingxiang Teng, Yunlong Liu, Ya-Dong Wang

BMC Systems Biology

DOI

章天骄

精选作品

期刊论文

CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images

MOTCS: A Cancer Subtype Classification and Key Biomarker Recognition Model Based on Multi-Omics Data Integration of Transformer

GMHAN: a heterogeneous graph attention framework for prioritizing coding and non-coding driver genes

spAttClu: a spatial domain clustering model leveraging spatially weighted graph attention and contrastive learning

SINTER3D: continuous 3D reconstruction of spatial transcriptomics via implicit neural representations

CellGAT: A GAT-Based Method for Constructing a Cell Communication Network Integrating Multiomics Information

IMAGO: An Improved Model Based on Attention Mechanism for Enhanced Protein Function Prediction

spaMGCN: a graph convolutional network with autoencoder for spatial domain identification using multi-scale adaptation

KansformerEPI: a deep learning framework integrating KAN and transformer for predicting enhancer–promoter interactions

SGCD: High‐Resolution Spatial Domain Characterization via Data Interpolation and Cell‐Type Deconvolution

CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data

Multi-omics single-cell data alignment and integration with enhanced contrastive learning and differential attention mechanism

Library size-stabilized metacells construction enhances co-expression network analysis in single-cell data

scDRMAE: integrating masked autoencoder with residual attention networks to leverage omics feature dependencies for accurate cell clustering

scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering

SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model

Utilizing Deep Neural Networks to Fill Gaps in Small Genomes

cfDiffusion: diffusion-based efficient generation of high quality scRNA-seq data with classifier-free guidance

DrugReSC: targeting disease-critical cell subpopulations with single-cell transcriptomic data for drug repurposing in cancer

scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data

GAADE: identification spatially variable genes based on adaptive graph attention network

VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell–cell communication network

GATv2EPI: Predicting Enhancer–Promoter Interactions with a Dynamic Graph Attention Network

CPPLS-MLP: a method for constructing cell–cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

基于IRS辅助的MIMO车联网系统联合波束成形设计

MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding

GTAD: a graph-based approach for cell spatial composition inference from integrated scRNA-seq and ST-seq data

DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA–Disease Association Prediction

Ground resource optimization for navigation constellation based on satellite link scheduling

[Review] Metaheuristics for the tabu clustered traveling salesman problem

基于排队论的D2D蜂窝异构网络的性能分析

Prioritization of disease microRNAs through a human phenome-microRNAome network