Hakutulokset - Xing‐Ming Zhao

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  1. 1
    <i>j</i>NMFMA: a joint non-negative matrix factorization meta-analysis of transcriptomics data

    <i>j</i>NMFMA: a joint non-negative matrix factorization meta-analysis of transcriptomics data Tekijä Hongqiang Wang, Chun-Hou Zheng, Xing‐Ming Zhao

    Julkaistu 2014
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  2. 2
    SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing

    SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing Tekijä Shaojun Pan, Xing‐Ming Zhao, Luís Pedro Coelho

    Julkaistu 2023
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  3. 3
    Detecting early-warning signals of type 1 diabetes and its leading biomolecular networks by dynamical network biomarkers

    Detecting early-warning signals of type 1 diabetes and its leading biomolecular networks by dynamical network biomarkers Tekijä Xiaoping Liu, Rui Liu, Xing-Ming Zhao, Luonan Chen

    Julkaistu 2013
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  4. 4
    Gene function prediction using labeled and unlabeled data

    Gene function prediction using labeled and unlabeled data Tekijä Xing‐Ming Zhao, Yong Wang, Luonan Chen, Kazuyuki Aihara

    Julkaistu 2008
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  5. 5
    Cellular transcriptional alterations of peripheral blood in Alzheimer’s disease

    Cellular transcriptional alterations of peripheral blood in Alzheimer’s disease Tekijä Liting Song, Yucheng Yang, Qihao Guo, Xing‐Ming Zhao

    Julkaistu 2022
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  6. 6
    The impact of physical exercise on adolescent social anxiety: the serial mediating effects of sports self-efficacy and expressive suppression

    The impact of physical exercise on adolescent social anxiety: the serial mediating effects of sports self-efficacy and expressive suppression Tekijä Jingtao Wu, Yanhong Shao, Jun Hu, Xing‐Ming Zhao

    Julkaistu 2025
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  7. 7
    APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility

    APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility Tekijä Junfeng Xia, Xing-Ming Zhao, Jiangning Song, De-Shuang Huang

    Julkaistu 2010
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  8. 8
    Uncovering signal transduction networks from high-throughput data by integer linear programming

    Uncovering signal transduction networks from high-throughput data by integer linear programming Tekijä Xing‐Ming Zhao, Rui‐Sheng Wang, Luonan Chen, Kazuyuki Aihara

    Julkaistu 2008
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  9. 9
    Identifying disease genes and module biomarkers by differential interactions

    Identifying disease genes and module biomarkers by differential interactions Tekijä Xiaoping Liu, Zhi-Ping Liu, Xing‐Ming Zhao, Luonan Chen

    Julkaistu 2011
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  10. 10
    A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments

    A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments Tekijä Shaojun Pan, Chengkai Zhu, Xing‐Ming Zhao, Luís Pedro Coelho

    Julkaistu 2022
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  11. 11
    Human Monogenic Disease Genes Have Frequently Functionally Redundant Paralogs

    Human Monogenic Disease Genes Have Frequently Functionally Redundant Paralogs Tekijä Wei‐Hua Chen, Xing‐Ming Zhao, Vera van Noort, Peer Bork

    Julkaistu 2013
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  12. 12
    DeepPhos: prediction of protein phosphorylation sites with deep learning

    DeepPhos: prediction of protein phosphorylation sites with deep learning Tekijä Fenglin Luo, Minghui Wang, Yu Liu, Xing-Ming Zhao, Ao Li

    Julkaistu 2018
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  13. 13
    A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank

    A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank Tekijä Guiying Dong, Jianfeng Feng, Fengzhu Sun, Jingqi Chen, Xing‐Ming Zhao

    Julkaistu 2021
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  14. 14
    PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein–protein interaction information

    PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein–protein interaction information Tekijä Hangyuan Yang, Minghui Wang, Xia Liu, Xing‐Ming Zhao, Ao Li

    Julkaistu 2021
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  15. 15
    Prediction of S-Glutathionylation Sites Based on Protein Sequences

    Prediction of S-Glutathionylation Sites Based on Protein Sequences Tekijä Chenglei Sun, Zheng-Zheng Shi, Xiaobo Zhou, Luonan Chen, Xing-Ming Zhao

    Julkaistu 2013
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  16. 16
    Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks

    Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks Tekijä Xiujun Zhang, Juan Zhao, Jin‐Kao Hao, Xing‐Ming Zhao, Luonan Chen

    Julkaistu 2014
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  17. 17
    OGEE v2: an update of the online gene essentiality database with special focus on differentially essential genes in human cancer cell lines

    OGEE v2: an update of the online gene essentiality database with special focus on differentially essential genes in human cancer cell lines Tekijä Wei‐Hua Chen, Guanting Lu, Xiaohong Chen, Xing‐Ming Zhao, Peer Bork

    Julkaistu 2016
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  18. 18
    Macrel: antimicrobial peptide screening in genomes and metagenomes

    Macrel: antimicrobial peptide screening in genomes and metagenomes Tekijä Célio Dias Santos Júnior, Shaojun Pan, Xing‐Ming Zhao, Luís Pedro Coelho

    Julkaistu 2020
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  19. 19
    Identifying dysregulated pathways in cancers from pathway interaction networks

    Identifying dysregulated pathways in cancers from pathway interaction networks Tekijä Ke-Qin Liu, Zhi-Ping Liu, Jin‐Kao Hao, Luonan Chen, Xing‐Ming Zhao

    Julkaistu 2012
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  20. 20
    Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets

    Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets Tekijä Mingjun Wang, Xing‐Ming Zhao, Hao Tan, Tatsuya Akutsu, James C. Whisstock, Jiangning Song

    Julkaistu 2013
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