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Paper Publications
[1] Prediction of human disease-associated phosphorylation sites with combined feature selection approach and support vector machine.IET SYSTEMS BIOLOGY.2015,9(4):155-163
[2] PKIS: computational identification of protein kinases for experimentally discovered protein phosphorylation sites.BMC BIOINFORMATICS.2013,14
[3] A novel method for identifying potential disease-related miRNAs via a disease-miRNA-target heterogeneous network.MOLECULAR BIOSYSTEMS.2017,13(11):2328-2337
[4] wangminghui.A novel method for predicting post-translational modifications on serine and threonine sites by using site-modification network profiles.MOLECULAR BIOSYSTEMS.2014,11(11):3092-3100
[5] wangminghui.ksrMKL: a novel method for identification of kinase-substrate relationships using multiple kernel learning.PEERJ.2017,5
[6] Prediction of kinase-substrate relations based on heterogeneous networks.JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY.2015,13(6)
[7] Prediction of protein kinase-specific phosphorylation sites in hierarchical structure using functional information and random forest.AMINO ACIDS.2014,46(4):1069-1078
[8] Improving the performance of protein kinase identification via high dimensional protein-protein interactions and substrate structure data.MOLECULAR BIOSYSTEMS.2013,10(3):694-702
[9] MPTM: A tool for mining protein post-translational modifications from literature.JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY.2017,15(5)
[10] wangminghui.A Novel Phosphorylation Site-Kinase Network-Based Method for the Accurate Prediction of Kinase-Substrate Relationships.BIOMED RESEARCH INTERNATIONAL.2016,2017
[11] Systematic Analysis and Prediction of In Situ Cross Talk of O-GlcNAcylation and Phosphorylation.BIOMED RESEARCH INTERNATIONAL.2014,2015
[12] A novel network-based computational method to predict protein phosphorylation on tyrosine sites.JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY.2015,13(6)
[13] Prediction of post-translational modification sites using multiple kernel support vector machine.PEERJ.2017,5
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