Search Results - "Zhu, You"

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  1. 1

    Healable and Recyclable Elastomers with Record‐High Mechanical Robustness, Unprecedented Crack Tolerance, and Superhigh Elastic Restorability by Li, Zequan, Zhu, You‐Liang, Niu, Wenwen, Yang, Xiao, Jiang, Zhiyong, Lu, Zhong‐Yuan, Liu, Xiaokong, Sun, Junqi

    Published in Advanced materials (Weinheim) (01-07-2021)
    “…Spider silk is one of the most robust natural materials, which has extremely high strength in combination with great toughness and good elasticity. Inspired by…”
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  2. 2

    MicroRNAs and complex diseases: from experimental results to computational models by Chen, Xing, Xie, Di, Zhao, Qi, You, Zhu-Hong

    Published in Briefings in bioinformatics (22-03-2019)
    “…Abstract Plenty of microRNAs (miRNAs) were discovered at a rapid pace in plants, green algae, viruses and animals. As one of the most important components in…”
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  3. 3

    Long non-coding RNAs and complex diseases: from experimental results to computational models by Chen, Xing, Yan, Chenggang Clarence, Zhang, Xu, You, Zhu-Hong

    Published in Briefings in bioinformatics (01-07-2017)
    “…Abstract LncRNAs have attracted lots of attentions from researchers worldwide in recent decades. With the rapid advances in both experimental technology and…”
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  4. 4

    In Situ Grown Silver–Polymer Framework with Coordination Complexes for Functional Artificial Tissues by Zhang, Songlin, Deng, Yibing, Libanori, Alberto, Zhou, Yihao, Yang, Jiachen, Tat, Trinny, Yang, Lin, Sun, Wanxin, Zheng, Peng, Zhu, You‐Liang, Chen, Jun, Tan, Swee Ching

    Published in Advanced materials (Weinheim) (01-06-2023)
    “…Self‐sensing actuators are critical to artificial robots with biomimetic proprio‐/exteroception properties of biological neuromuscular systems. Existing add‐on…”
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  5. 5

    Distributed Winner-Take-All in Dynamic Networks by Li, Shuai, Zhou, MengChu, Luo, Xin, You, Zhu-Hong

    Published in IEEE transactions on automatic control (01-02-2017)
    “…This paper is concerned with the winner-take-all (WTA) problem on networks. We propose the first distributed protocol to address this problem dynamically. This…”
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  6. 6

    A "Molecular Water Pipe": A Giant Tubular Cluster {Dy72} Exhibits Fast Proton Transport and Slow Magnetic Relaxation by Qin, Lei, Yu, You-Zhu, Liao, Pei-Qin, Xue, Wei, Zheng, Zhiping, Chen, Xiao-Ming, Zheng, Yan-Zhen

    Published in Advanced materials (Weinheim) (01-12-2016)
    “…A lanthanide cluster, PCC‐72, which is the second largest, with 72 Dy(III) ions assembled into an unprecedented tubular structure, is synthesized. Remarkably,…”
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  7. 7

    BNPMDA: Bipartite Network Projection for MiRNA-Disease Association prediction by Chen, Xing, Xie, Di, Wang, Lei, Zhao, Qi, You, Zhu-Hong, Liu, Hongsheng

    Published in Bioinformatics (15-09-2018)
    “…Abstract Motivation A large number of resources have been devoted to exploring the associations between microRNAs (miRNAs) and diseases in the recent years…”
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  8. 8

    PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction by You, Zhu-Hong, Huang, Zhi-An, Zhu, Zexuan, Yan, Gui-Ying, Li, Zheng-Wei, Wen, Zhenkun, Chen, Xing

    Published in PLoS computational biology (01-03-2017)
    “…In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological…”
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  9. 9

    HiSCF: leveraging higher-order structures for clustering analysis in biological networks by Hu, Lun, Zhang, Jun, Pan, Xiangyu, Yan, Hong, You, Zhu-Hong

    Published in Bioinformatics (01-05-2021)
    “…Abstract Motivation Clustering analysis in a biological network is to group biological entities into functional modules, thus providing valuable insight into…”
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  10. 10

    A graph auto-encoder model for miRNA-disease associations prediction by Li, Zhengwei, Li, Jiashu, Nie, Ru, You, Zhu-Hong, Bao, Wenzheng

    Published in Briefings in bioinformatics (01-07-2021)
    “…Abstract Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases…”
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  11. 11

    Hierarchical graph attention network for miRNA-disease association prediction by Li, Zhengwei, Zhong, Tangbo, Huang, Deshuang, You, Zhu-Hong, Nie, Ru

    Published in Molecular therapy (06-04-2022)
    “…Many biological studies show that the mutation and abnormal expression of microRNAs (miRNAs) could cause a variety of diseases. As an important biomarker for…”
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  12. 12

    GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm by Wang, Lei, You, Zhu-Hong, Li, Yang-Ming, Zheng, Kai, Huang, Yu-An

    Published in PLoS computational biology (20-05-2020)
    “…Numerous evidences indicate that Circular RNAs (circRNAs) are widely involved in the occurrence and development of diseases. Identifying the association…”
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  13. 13

    Graph representation learning in bioinformatics: trends, methods and applications by Yi, Hai-Cheng, You, Zhu-Hong, Huang, De-Shuang, Kwoh, Chee Keong

    Published in Briefings in bioinformatics (17-01-2022)
    “…Abstract Graph is a natural data structure for describing complex systems, which contains a set of objects and relationships. Ubiquitous real-life biomedical…”
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  14. 14

    HINGRL: predicting drug–disease associations with graph representation learning on heterogeneous information networks by Zhao, Bo-Wei, Hu, Lun, You, Zhu-Hong, Wang, Lei, Su, Xiao-Rui

    Published in Briefings in bioinformatics (17-01-2022)
    “…Abstract Identifying new indications for drugs plays an essential role at many phases of drug research and development. Computational methods are regarded as…”
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  15. 15

    Ultrasmall Single‐Chain Nanoparticles Derived from Amphiphilic Alternating Copolymers by Qi, Chufeng, Zhu, You‐Liang, Zhao, Huanyu, Lu, Zhong‐Yuan

    Published in Macromolecular rapid communications. (01-07-2024)
    “…The collapse or folding of an individual polymer chain into a nanoscale particle gives rise to single‐chain nanoparticles (SCNPs), which share a soft nature…”
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  16. 16

    GALAMOST: GPU-accelerated large-scale molecular simulation toolkit by Zhu, You-Liang, Liu, Hong, Li, Zhan-Wei, Qian, Hu-Jun, Milano, Giuseppe, Lu, Zhong-Yuan

    Published in Journal of computational chemistry (30-09-2013)
    “…GALAMOST [graphics processing unit (GPU)‐accelerated large‐scale molecular simulation toolkit] is a molecular simulation package designed to utilize the…”
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  17. 17

    Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest by You, Zhu-Hong, Chan, Keith C C, Hu, Pengwei

    Published in PloS one (06-05-2015)
    “…The study of protein-protein interactions (PPIs) can be very important for the understanding of biological cellular functions. However, detecting PPIs in the…”
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  18. 18

    WBSMDA: Within and Between Score for MiRNA-Disease Association prediction by Chen, Xing, Yan, Chenggang Clarence, Zhang, Xu, You, Zhu-Hong, Deng, Lixi, Liu, Ying, Zhang, Yongdong, Dai, Qionghai

    Published in Scientific reports (16-02-2016)
    “…Increasing evidences have indicated that microRNAs (miRNAs) are functionally associated with the development and progression of various complex human diseases…”
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  19. 19

    A survey on computational models for predicting protein-protein interactions by Hu, Lun, Wang, Xiaojuan, Huang, Yu-An, Hu, Pengwei, You, Zhu-Hong

    Published in Briefings in bioinformatics (02-09-2021)
    “…Proteins interact with each other to play critical roles in many biological processes in cells. Although promising, laboratory experiments usually suffer from…”
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  20. 20

    Highly Efficient Framework for Predicting Interactions Between Proteins by You, Zhu-Hong, Zhou, MengChu, Luo, Xin, Li, Shuai

    Published in IEEE transactions on cybernetics (01-03-2017)
    “…Protein-protein interactions (PPIs) play a central role in many biological processes. Although a large amount of human PPI data has been generated by…”
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