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Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism.

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第一作者： Wei,Peng

第一单位： Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650050, China. weipeng1980@gmail.com.;Computer Technology Application Key Lab of Yunnan Province, Kunming University of Science and Technology, Kunming, 650050, China. weipeng1980@gmail.com.

作者： Wei,Peng ^[1] ; Rong,Wu ^[2] ; Wei,Dai ^[3] ; Ning,Yu ^[4]

作者单位： Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650050, China. weipeng1980@gmail.com.;Computer Technology Application Key Lab of Yunnan Province, Kunming University of Science and Technology, Kunming, 650050, China. weipeng1980@gmail.com. ^[1] Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650050, China. ^[2] Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650050, China.;Computer Technology Application Key Lab of Yunnan Province, Kunming University of Science and Technology, Kunming, 650050, China. ^[3] Department of Computing Sciences, The College at Brockport, State University of New York, 350 New Campus Drive, Brockport, NY, 14422, USA. ^[4]

关键词 Cancer driver genes Feature fusion Heterogeneous graph convolutional neural networks Multi-view heterogeneous network embedding Network integration

医学主题词人类(Humans);算法(Algorithms);癌基因(Oncogenes);微RNAs(MicroRNAs);基因组学(Genomics);肿瘤(Neoplasms)

DOI 10.1186/s12859-023-05140-3

PMID 36639646

发布时间 2023-01-17

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准确一般字义偏差语意偏离译文作用小提交