Nature Communications (Feb 2023)
Single-cell biological network inference using a heterogeneous graph transformer
- Anjun Ma,
- Xiaoying Wang,
- Jingxian Li,
- Cankun Wang,
- Tong Xiao,
- Yuntao Liu,
- Hao Cheng,
- Juexin Wang,
- Yang Li,
- Yuzhou Chang,
- Jinpu Li,
- Duolin Wang,
- Yuexu Jiang,
- Li Su,
- Gang Xin,
- Shaopeng Gu,
- Zihai Li,
- Bingqiang Liu,
- Dong Xu,
- Qin Ma
Affiliations
- Anjun Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- Xiaoying Wang
- School of Mathematics, Shandong University
- Jingxian Li
- School of Mathematics, Shandong University
- Cankun Wang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- Tong Xiao
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University
- Yuntao Liu
- School of Mathematics, Shandong University
- Hao Cheng
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- Juexin Wang
- Department of Electrical Engineering and Computer Science, University of Missouri
- Yang Li
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- Yuzhou Chang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- Jinpu Li
- Christopher S. Bond Life Sciences Center, University of Missouri
- Duolin Wang
- Department of Electrical Engineering and Computer Science, University of Missouri
- Yuexu Jiang
- Department of Electrical Engineering and Computer Science, University of Missouri
- Li Su
- Christopher S. Bond Life Sciences Center, University of Missouri
- Gang Xin
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University
- Shaopeng Gu
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- Zihai Li
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University
- Bingqiang Liu
- School of Mathematics, Shandong University
- Dong Xu
- Department of Electrical Engineering and Computer Science, University of Missouri
- Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University
- DOI
- https://doi.org/10.1038/s41467-023-36559-0
- Journal volume & issue
-
Vol. 14,
no. 1
pp. 1 – 18
Abstract
Single-cell multi-omics and deep learning could lead to the inference of biological networks across specific cell types. Here, the authors develop DeepMAPS, a deep learning, graph-based approach for cell-type specific network inference from single-cell multi-omics data that is tested on healthy and tumour tissue datasets.
