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Recently, deep learning (DL)\u2013based methods have been proposed to infer GRNs from single-cell transcriptomic data and achieved impressive performance. However, these methods do not fully utilize graph topological information and high-order neighbor information from multiple receptive fields. To overcome those limitations, we propose a novel model based on multiview graph attention network, namely, scMGATGRN, to infer GRNs. scMGATGRN mainly consists of GAT, multiview, and view-level attention mechanism. GAT can extract essential features of the gene regulatory network. The multiview model can simultaneously utilize local feature information and high-order neighbor feature information of nodes in the gene regulatory network. The view-level attention mechanism dynamically adjusts the relative importance of node embedding representations and efficiently aggregates node embedding representations from two views. To verify the effectiveness of scMGATGRN, we compared its performance with 10 methods (five shallow learning algorithms and five state-of-the-art DL-based methods) on seven benchmark single-cell RNA sequencing (scRNA-seq) datasets from five cell lines (two in human and three in mouse) with four different kinds of ground-truth networks. The experimental results not only show that scMGATGRN outperforms competing methods but also demonstrate the potential of this model in inferring GRNs. The code and data of scMGATGRN are made freely available on GitHub (https:\/\/github.com\/nathanyl\/scMGATGRN).<\/jats:p>","DOI":"10.1093\/bib\/bbae526","type":"journal-article","created":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T09:15:30Z","timestamp":1729156530000},"source":"Crossref","is-referenced-by-count":56,"title":["scMGATGRN: a multiview graph attention network\u2013based method for inferring gene regulatory networks from single-cell transcriptomic data"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9694-8191","authenticated-orcid":false,"given":"Lin","family":"Yuan","sequence":"first","affiliation":[{"name":"Key Laboratory of Computing Power Network and Information Security , Ministry of Education, Shandong Computer Science Center, , 3501 Daxue Road, 250353, Shandong ,","place":["China"]},{"name":"Qilu University of Technology (Shandong Academy of Sciences) , Ministry of Education, Shandong Computer Science Center, , 3501 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Education, Shandong Computer Science Center, , 3501 Daxue Road, 250353, Shandong ,","place":["China"]},{"name":"Shandong Engineering Research Center of Big Data Applied Technology , Faculty of Computer Science and Technology, , 3501 Daxue Road, 250353, Shandong ,","place":["China"]},{"name":"Qilu University of Technology (Shandong Academy of Sciences) , Faculty of Computer Science and Technology, , 3501 Daxue Road, 250353, Shandong ,","place":["China"]},{"name":"Shandong Provincial Key Laboratory of Industrial Network and Information System Security , Shandong Fundamental Research Center for Computer Science, 3501 Daxue Road, 250353, Shandong ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7572-9195","authenticated-orcid":false,"given":"Zhen","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer and Software , , 80 Changjiang Road, 473004, Henan ,","place":["China"]},{"name":"Nanyang Institute of Technology , , 80 Changjiang Road, 473004, Henan ,","place":["China"]}]},{"given":"Qinhu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Ningbo Institute of Digital Twin , , 568 Tongxin Road, 315201, Zhejiang ,","place":["China"]},{"name":"Eastern Institute of Technology , , 568 Tongxin Road, 315201, Zhejiang ,","place":["China"]}]},{"given":"Ming","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Pediatrics , , 201 Hubinnan Road, 361004, Fujian ,","place":["China"]},{"name":"Zhongshan Hospital Xiamen University , , 201 Hubinnan Road, 361004, Fujian ,","place":["China"]}]},{"given":"Chun-Hou","family":"Zheng","sequence":"additional","affiliation":[{"name":"Key Lab of Intelligent Computing and Signal Processing of Ministry of Education , School of Artificial Intelligence, , 111 Jiulong Road, 230601, Anhui ,","place":["China"]},{"name":"Anhui University , School of Artificial Intelligence, , 111 Jiulong Road, 230601, Anhui 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