Hasil Pencarian - Ling-Yun Dai

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  1. 1
    Two photon couplings of the lightest isoscalars from BELLE data

    Two photon couplings of the lightest isoscalars from BELLE data oleh Ling-Yun Dai, M.R. Pennington

    Diterbitkan 2014-09-01
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  2. 2
    Joint Nonnegative Matrix Factorization Based on Sparse and Graph Laplacian Regularization for Clustering and Co-Differential Expression Genes Analysis

    Joint Nonnegative Matrix Factorization Based on Sparse and Graph Laplacian Regularization for Clustering and Co-Differential Expression Genes Analysis oleh Ling-Yun Dai, Rong Zhu, Juan Wang

    Diterbitkan 2020-01-01
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  3. 3
    Two and three pseudoscalar production in e + e − annihilation and their contributions to (g − 2) μ

    Two and three pseudoscalar production in e + e − annihilation and their contributions to (g − 2) μ oleh Wen Qin, Ling-Yun Dai, Jorge Portolés

    Diterbitkan 2021-03-01
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  4. 4
    Antinucleon-nucleon interaction at next-to-next-to-next-to-leading order in chiral effective field theory

    Antinucleon-nucleon interaction at next-to-next-to-next-to-leading order in chiral effective field theory oleh Ling-Yun Dai, Johann Haidenbauer, Ulf-G. Meißner

    Diterbitkan 2017-07-01
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  5. 5
    Two body final states production in electron-positron annihilation and their contributions to (g − 2) μ

    Two body final states production in electron-positron annihilation and their contributions to (g − 2) μ oleh Shi-Jia Wang, Zhen Fang, Ling-Yun Dai

    Diterbitkan 2023-07-01
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  6. 6
    Predicting miRNA-disease associations via layer attention graph convolutional network model

    Predicting miRNA-disease associations via layer attention graph convolutional network model oleh Han Han, Rong Zhu, Jin-Xing Liu, Ling-Yun Dai

    Diterbitkan 2022-03-01
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  7. 7
    IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier

    IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier oleh Rong Zhu, Yong Wang, Jin-Xing Liu, Ling-Yun Dai

    Diterbitkan 2021-04-01
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  8. 8
    Joint Topics on Exotic Hadron States and Heavy Flavor Hadronic Decay

    Joint Topics on Exotic Hadron States and Heavy Flavor Hadronic Decay oleh Xian-Wei Kang, J. A. Oller, Ling-Yun Dai, Tao Luo

    Diterbitkan 2019-01-01
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  9. 9
    ACCBN: ant-Colony-clustering-based bipartite network method for predicting long non-coding RNA–protein interactions

    ACCBN: ant-Colony-clustering-based bipartite network method for predicting long non-coding RNA–protein interactions oleh Rong Zhu, Guangshun Li, Jin-Xing Liu, Ling-Yun Dai, Ying Guo

    Diterbitkan 2019-01-01
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  10. 10
    Pole analysis on the hadron spectroscopy of $$\Lambda _b\rightarrow J/\Psi p K^-$$ Λb→J/ΨpK-

    Pole analysis on the hadron spectroscopy of $$\Lambda _b\rightarrow J/\Psi p K^-$$ Λb→J/ΨpK- oleh Shi-Qing Kuang, Ling-Yun Dai, Xian-Wei Kang, De-Liang Yao

    Diterbitkan 2020-05-01
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  11. 11
    Semileptonic B and $$B_s$$ Bs decays involving scalar and axial-vector mesons

    Semileptonic B and $$B_s$$ Bs decays involving scalar and axial-vector mesons oleh Xian-Wei Kang, Tao Luo, Yi Zhang, Ling-Yun Dai, Chao Wang

    Diterbitkan 2018-11-01
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  12. 12
    Strong decays of $$T^a_{c{\bar{s}0}}(2900)^{++/0}$$ T c s ¯ 0 a ( 2900 ) + + / 0 as a fully open-flavor tetraquark state

    Strong decays of $$T^a_{c{\bar{s}0}}(2900)^{++/0}$$ T c s ¯ 0 a ( 2900 ) + + / 0 as a fully open-flavor tetraquark state oleh Ding-Kun Lian, Wei Chen, Hua-Xing Chen, Ling-Yun Dai, T. G. Steele

    Diterbitkan 2024-01-01
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  13. 13
    Study of X(6900) with unitarized coupled channel scattering amplitudes

    Study of X(6900) with unitarized coupled channel scattering amplitudes oleh Shi-Qing Kuang, Qi Zhou, Di Guo, Qin-He Yang, Ling-Yun Dai

    Diterbitkan 2023-05-01
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  14. 14
    L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions

    L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions oleh Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Sha-Sha Yuan

    Diterbitkan 2019-06-01
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  15. 15
    PCA via joint graph Laplacian and sparse constraint: Identification of differentially expressed genes and sample clustering on gene expression data

    PCA via joint graph Laplacian and sparse constraint: Identification of differentially expressed genes and sample clustering on gene expression data oleh Chun-Mei Feng, Yong Xu, Mi-Xiao Hou, Ling-Yun Dai, Jun-Liang Shang

    Diterbitkan 2019-12-01
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  16. 16
    Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints

    Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints oleh Juan Wang, Cong-Hai Lu, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong

    Diterbitkan 2019-12-01
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  17. 17
    The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method

    The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method oleh Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang, Ling-Yun Dai

    Diterbitkan 2019-01-01
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  18. 18
    Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data

    Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data oleh Juan Wang, Cong-Hai Lu, Xiang-Zhen Kong, Ling-Yun Dai, Shasha Yuan, Xiaofeng Zhang

    Diterbitkan 2022-01-01
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  19. 19
    Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection

    Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection oleh Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu

    Diterbitkan 2019-01-01
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  20. 20
    Study of the electromagnetic form factors of the nucleons in the timelike region

    Study of the electromagnetic form factors of the nucleons in the timelike region oleh Qin-He Yang, Di Guo, Ming-Yan Li, Ling-Yun Dai, Johann Haidenbauer, Ulf-G. Meißner

    Diterbitkan 2024-08-01
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