SpaGraphCCI: Spatial cell-cell communication inference through GAT-based co-convolutional feature integration

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成果类型：

期刊论文

作者：

Zhang, Han;Cui, Ting;Xu, Xiaoqiang;Sui, Guangyu;Fang, Qiaoli;...

通讯作者：

Shang, DS;Lv, YF

作者机构：

[Fang, Qiaoli; Shang, Desi; Zhang, Han; Yang, Guanghao] Univ South China, Sch Comp, Hengyang, Hunan, Peoples R China.

[Fang, Qiaoli; Shang, Desi; Zhang, Han; Yang, Guanghao; Cui, Ting; Xu, Xiaoqiang; Gong, Yizhen] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Cardiovasc Lab Big Data & Imaging Artificial Intel, Hengyang, Hunan, Peoples R China.

[Fang, Qiaoli; Shang, Desi; Zhang, Han; Yang, Guanghao; Cui, Ting; Xu, Xiaoqiang; Gong, Yizhen] Univ South China, Hunan Prov Key Lab Multi & Artificial Intelligence, Hengyang, Hunan, Peoples R China.

[Shang, Desi; Cui, Ting; Xu, Xiaoqiang; Gong, Yizhen] Univ South China, Sch Basic Med Sci, Hengyang Med Sch, Dept Biochem & Mol Biol, Hengyang, Hunan, Peoples R China.

[Shang, Desi; Xu, Xiaoqiang] Univ South China, Affiliated Hosp 1, Inst Cardiovasc Dis, Hengyang Med Sch, Hengyang, Hunan, Peoples R China.

通讯机构：

[Shang, DS ; Lv, YF ] U

Univ South China, Sch Comp, Hengyang, Hunan, Peoples R China.

Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Cardiovasc Lab Big Data & Imaging Artificial Intel, Hengyang, Hunan, Peoples R China.

Univ South China, Hunan Prov Key Lab Multi & Artificial Intelligence, Hengyang, Hunan, Peoples R China.

Univ South China, Sch Basic Med Sci, Hengyang Med Sch, Dept Biochem & Mol Biol, Hengyang, Hunan, Peoples R China.

语种：

英文

关键词：

bioinformatics;feature extraction;graphs;learning (artificial intelligence)

期刊：

IET Systems Biology

ISSN：

1751-8849

年：

2025

卷：

期：

页码：

e70000

DOI：

10.1049/syb2.70000

基金类别：

Clinical Research 4310 Programme of the First Affiliated Hospital of the University of South China [62272211]; National Natural Science Foundation of China [2024JJ6395, 2023JJ30535]; Natural Science Foundation of Hunan Province [2023TP1047, 20224310NHYCG05]; Innovation Platform and Talent Programme

机构署名：

本校为第一且通讯机构

院系归属：

化学化工学院

医学院

药学与生物科学学院

摘要：

Spatially resolved transcriptomics technologies potentially provide the extra spatial position information and tissue image to better inferspatial cell-cell interactions (CCIs) in processes such as tissue homeostasis, development, and disease progression. However, methods for effectively integrating spatial multimodal data to infer CCIs are still lacking. Here, the authors propose a deep learning method for integrating features through co-convolution, called SpaGraphCCI, to effectively integrate data from different modalities of SRT by projecting gene expression and image feature into a low-di...

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SpaGraphCCI: Spatial cell-cell communication inference through GAT-based co-convolutional feature integration

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