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Discovering miRNAs Associated With Multiple Sclerosis Based on Network Representation Learning and Deep Learning Methods [PDF]
Frontiers in Genetics, 2022 Identifying biomarkers of Multiple Sclerosis is important for the diagnosis and treatment of Multiple Sclerosis. The existing study has shown that miRNA is one of the most important biomarkers for diseases.
Xiaoping Sun +6 more
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Identifying Disease Related Genes by Network Representation and Convolutional Neural Network [PDF]
Frontiers in Cell and Developmental Biology, 2021 The identification of disease related genes plays essential roles in bioinformatics. To achieve this, many powerful machine learning methods have been proposed from various computational aspects, such as biological network analysis, classification ...
Bolin Chen +5 more
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Network Representation Learning: A Survey [PDF]
IEEE Transactions on Big Data, 2020 Accepted by IEEE transactions on Big Data; 25 pages, 10 tables, 6 figures and 127 ...
Daokun Zhang, Jie Yin, Xingquan Zhu
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Multi-Task Network Representation Learning [PDF]
Frontiers in Neuroscience, 2020 Networks, such as social networks, biochemical networks, and protein-protein interaction networks are ubiquitous in the real world. Network representation learning aims to embed nodes in a network as low-dimensional, dense, real-valued vectors, and ...
Yu Xie +4 more
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Network Representation Based on the Joint Learning of Three Feature Views
Big Data Mining and Analytics, 2019 Network representation learning plays an important role in the field of network data mining. By embedding network structures and other features into the representation vector space of low dimensions, network representation learning algorithms can provide
Zhonglin Ye +4 more
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Social Network Forensics Analysis Model Based on Network Representation Learning [PDF]
EntropyThe rapid evolution of computer technology and social networks has led to massive data generation through interpersonal communications, necessitating improved methods for information mining and relational analysis in areas such as criminal activity. This
Kuo Zhao +6 more
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Evaluation for Instructional Interaction Using Bipartite Network Representation Learning [PDF]
Jisuanji kexue yu tansuo, 2023 With the combination and development of “Internet plus Education”, online education has become an important teaching mode at present. Research shows that the interaction in online education provides effective help for learners.
WANG Xuecen, ZHANG Yu, ZHAO Changkuan, CHEN Mo, YU Ge
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Altered brain functional connectivity in vegetative state and minimally conscious state
Frontiers in Aging Neuroscience, 2023 ObjectivesThe pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there is a high rate of misdiagnosis for subtypes of DoC.
Yi Yang +10 more
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Shanghai Jiaotong Daxue xuebao, 2021 Aimed at the problem that the traditional meta-path random walk in heterogeneous network representation cannot accurately describe the heterogeneous network structure and cannot capture the true distribution of network nodes well, a heterogeneous network
YUAN Ming, LIU Qun, SUN Haichao, TAN Hongsheng
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Design representation as semantic networks
Computers in Industry, 2023 Design representation is a common task in the design process to facilitate learning, analysis, redesign, communication, and other design activities. Traditional representation techniques rely on human expertise and manual construction and are difficult to repeat and scale.
Serhad Sarica, Ji Han, Jianxi Luo
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