Rezultaty - Ling‐Yun Wu

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  1. 1
    Efficient methods for identifying mutated driver pathways in cancer

    Efficient methods for identifying mutated driver pathways in cancer od Junfei Zhao, Shihua Zhang, Ling‐Yun Wu, Yu Xia

    Wydane 2012
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  2. 2
    iSNO-PseAAC: Predict Cysteine S-Nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition

    iSNO-PseAAC: Predict Cysteine S-Nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition od Yan Xu, Jun Ding, Ling‐Yun Wu, Kuo‐Chen Chou

    Wydane 2013
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  3. 3
    Discovery of co-occurring driver pathways in cancer

    Discovery of co-occurring driver pathways in cancer od Junhua Zhang, Ling-Yun Wu, Xiang-Sun Zhang, Shihua Zhang

    Wydane 2014
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  4. 4
    Prediction of protein–RNA binding sites by a random forest method with combined features

    Prediction of protein–RNA binding sites by a random forest method with combined features od Zhiping Liu, Ling‐Yun Wu, Yong Wang, Yu Xia, Luonan Chen

    Wydane 2010
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  5. 5
    Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection

    Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection od Yan Xu, Ya-Xin Ding, Jun Ding, Ling‐Yun Wu, Yu Xue

    Wydane 2016
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  6. 6
    iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine<i>S</i>-nitrosylation sites in proteins

    iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine<i>S</i>-nitrosylation sites in proteins od Yan Xu, Xiaojian Shao, Ling‐Yun Wu, Nai-Yang Deng, Kuo‐Chen Chou

    Wydane 2013
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  7. 7
    iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition

    iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition od Yan Xu, Xin Wen, Wen Lishu, Ling‐Yun Wu, Nai-Yang Deng, Kuo‐Chen Chou

    Wydane 2014
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  8. 8
    Feature Extraction and Identification of Alzheimer’s Disease based on Latent Factor of Multi-Channel EEG

    Feature Extraction and Identification of Alzheimer’s Disease based on Latent Factor of Multi-Channel EEG od Kai Li, Jiang Wang, Shanshan Li, Haitao Yu, Lin Zhu, Jing Liu, Ling‐Yun Wu

    Wydane 2021
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  9. 9
    iSuc-PseAAC: predicting lysine succinylation in proteins by incorporating peptide position-specific propensity

    iSuc-PseAAC: predicting lysine succinylation in proteins by incorporating peptide position-specific propensity od Yan Xu, Ya-Xin Ding, Jun Ding, Ya-Hui Lei, Ling‐Yun Wu, Nai-Yang Deng

    Wydane 2015
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  10. 10
    NOA: a novel Network Ontology Analysis method

    NOA: a novel Network Ontology Analysis method od Jiguang Wang, Qiang Huang, Zhi-Ping Liu, Yong Wang, Ling‐Yun Wu, Luonan Chen, Xiang‐Sun Zhang

    Wydane 2011
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  11. 11
    Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism

    Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism od Péter Csermely, János Hódsági, Tamás Korcsmáros, Dezső Módos, Áron R. Perez-Lopez, Kristóf Z. Szalay, Dániel V. Veres, Katalin Lenti, Ling‐Yun Wu, Yu Xia

    Wydane 2014
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  12. 12
    Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism: network models, novel therapeutic target strategies, and the contributions of hypoxia, inflammation and cellular senescence.

    Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism: network models, novel therapeutic target strategies, and th... od Péter Csermely, János Hódsági, Tamás Korcsmáros, Dezső Módos, Áron R. Perez-Lopez, Kristóf Z. Szalay, Dániel V. Veres, Katalin Lenti, Ling Yun Wu, Xiang-Sun Zhang

    Wydane 2015
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  13. 13
    Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data

    Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data od Duanchen Sun, Xiangnan Guan, Amy E. Moran, Ling‐Yun Wu, David Z. Qian, Pepper Schedin, Mu‐Shui Dai, Alexey V. Danilov, Joshi J. Alumkal, Andrew Adey, Paul T. Spellman, Zheng Xia

    Wydane 2021
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