Simon

Leyi WEI

Ph.D., Professor

Member of IEEE, ACM, CAAI

Email: weileyi [at] sdu (dot) edu (dot) cn

Address: Room 105, Adminstrator Bld., Shandong University, Jinan, Shandong, China

Post code:250101

 

Biography

Leyi Wei recieved the B.Sc. in Computing Mathematics from Xiamen University in 2010, the M.E. and Ph.D. degrees in Computer Science and Technology from Xiamen University in 2013 and in 2016, respectively.SInce 2020.01 till now, He is a Professor at School of Software, Shandong University. Before that, he worked as an Assitant Professor in College of Intelligence and Computing, Tianjin University. He also worked as a project researcher in the lab of Functional analysis in silico, Institute of Medical Science, University of Tokyo during 2018 - 2019.

Research Interests

My research interests include Bioinformatics, Machine Learning, Deep Learning, and Computational Biology. Specifically, I am interested in designing new computational methods to address several Bioinformatics problems based on deep learning and other artificial intelligence techniques.

Recruitment

I'm looking for talented and motivated undergraduate and graduate students. If you are interested in Machine Learning, Deep Learning, and Bioinformatics, please feel free to contact with me!

现招收2020级硕士研究生,欢迎报考!另外,常年寻找对科研感兴趣的本科生和研究生进入我的团队,如果你对机器学习、深度学习、生物信息学等方向感兴趣,请邮件与我联系。进入实验室后,我将提供一对一指导!

Publications (Selected)

#: indicating equal contribution. *: indicating corresponding author.

    2020

  1. Zengyan Hong, Xiangxiang Zeng*, Leyi Wei*, Xiangrong Liu*
    Identifying enhancer–promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism.
    Bioinformatics, 2020. (SCI, JCR-2, IF2018=4.531). In press.
    [PDF]

  2. Jing Li, Leyi Wei, Fei Guo*, Quan Zou*
    EP3: an ensemble predictor that accurately identifies type III secreted effectors
    Briefings in bioinformatics, 2020. (SCI, JCR-1, IF2018=9.101). In press.
    [PDF]

  3. Ran Su*, Jiahang Zhang, Xiaofeng Liu*, Leyi Wei*
    Identification of expression signatures for non-small-cell lung carcinoma subtype classification.
    Bioinformatics, 2020. (SCI, JCR-2, IF2018=4.531). In press.
    [PDF]

    2019

  1. Ran Su*, Huichen Wu, Xinyi Liu, Leyi Wei*
    Predicting drug-induced hepatotoxicity based on biological feature maps and diverse classification strategies.
    Briefings in bioinformatics, 2019. (SCI, JCR-1, IF2018=9.101). In press.
    [PDF]

  2. Leyi Wei, Ran Su, Shasha Luan, Zhijun Liao, Balachandran Manavalan*, Quan Zou*, Xiaolong Shi*
    Iterative feature representations improve N4-methylcytosine site prediction.
    Bioinformatics, 2019. (SCI, JCR-2, IF2018=4.531). In press.
    [PDF]

  3. Bing Rao, Chen Zhou, Guoying Zhang*, Ran Su*, Leyi Wei*
    ACPred-Fuse: fusing multi-view information improves the prediction of anticancer peptides.
    Briefings in bioinformatics, 2019. (SCI, JCR-1, IF2018=9.101). In press.
    [PDF]

  4. Leyi Wei, Chen Zhou, Ran Su*, Quan Zou*
    PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning.
    Bioinformatics, 2019. (SCI, JCR-2, IF2018=4.531). In press.
    [PDF]

  5. Fuyi Li*, Cunshuo Fan, Tatiana T Marquez-Lago, André Leier, Jerico Revote, Cangzhi Jia, Yan Zhu, A Ian Smith, Geoffrey I Webb, Quanzhong Liu*, Leyi Wei*, Jian Li, Jiangning Song*
    PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.
    Briefings in bioinformatics, 2019. (SCI, JCR-1, IF2018=9.101). In press.
    [PDF]

  6. Ran Su, Xinyi Liu, Guobao Xiao*, Leyi Wei*
    Meta-GDBP: a high-level stacked regression model to improve anticancer drug response prediction.
    Briefings in bioinformatics, 2019. (SCI, JCR-1, IF2018=9.101). In press.
    [PDF]

  7. Ran Su, Xinyi Liu, Leyi Wei*
    MinE-RFE: determine the optimal subset from RFE by minimizing the subset-accuracy–defined energy.
    Briefings in bioinformatics, 2019. (SCI, JCR-1, IF2018=9.101). In press.
    [PDF]

    2018

  1. B. Manavalan, S. Basith, T.H. Shin, Leyi Wei*, G. Lee*
    mAHTPred: a sequence-based meta predictor for improving the prediction of antihypertensive peptides using effective feature representation.
    Bioinformatics. 2018. (SCI, JCR-2, IF2016=7.307). In press.
    [PDF]

  2. Ran Su, Jie Hu, Quan Zou, Balachandran Manavalana*, and Leyi Wei*,
    Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools.
    Briefings in Bioinformatics. 2018. (SCI, JCR-1, IF2017=6.302). In press.

    [PDF]

  3. Leyi Wei, Jie Hu, Fuyi Li, Jiangning Song*, Ran Su*, and Quan Zou*.
    Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms.
    Briefings in Bioinformatics. 2018. (SCI, JCR-1, IF2017=6.302). In press.

    [Server] | [PDF]

  4. Leyi Wei, Shasha Luan, Luis Augusto Eijy Nagai, Ran Su*, and Quan Zou*.
    Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species.
    Bioinformatics. 2018. (SCI, JCR-2, IF2016=7.307)

    [Server] | [PDF]

  5. Xiaoli Qiang, Chen Zhou, Xiucai Ye, Pufeng Du, Ran Su*, and Leyi Wei*.

    CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning.
    Briefings in Bioinformatics. 2018. (SCI, JCR-1, IF2017=6.302). In press. DOI: 10.1093/bib/bby091.
    [Server] | [PDF]

  6. Ran Su, Huichen Wu, Bo Xu, Xiaofeng Liu, Leyi Wei*.
    Developing a Multi-Dose Computational Model for Drug-induced Hepatotoxicity Prediction based on Toxicogenomics Data.
    IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2018. (SCI, IF2016=1.955). In press.
    [PDF]

  7. Leyi Wei, Huangrong Chen, and Ran Su*.
    M6APred-EL: A sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning.
    Molecular Therapy - Nucleic Acids. 2018. 12: 635-644 (SCI, JCR-2, IF2016=6.392)..
    [Server] | [PDF]

  8. Leyi Wei*, Chen Zhou, Huangrong Chen, Jiangning Song*, and Ran Su*.
    ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides.
    Bioinformatics. 2018. (SCI, JCR-2, IF2016=7.307). In press.
    [Server] | [PDF]

  9. Leyi Wei, Ran Su, Pengwei Xing, Bing Wang, Xiuting Li, and Quan Zou*.

    Integration of deep feature representations to improve the prediction of N6-methyladenosine sites.
    Neurocomputing. 2018. (SCI, JCR-2, IF2016=3.317). In press.
    [Server] | [PDF]

  10. Leyi Wei, Yijie Ding, Ran Su, Jijun Tang, and Quan Zou*.
    Prediction of human protein subcellular localization using deep learning.
    BIBM 2019. (CCF-B).

    [PDF]
  11. 2017

  12. Leyi Wei, Pengwei Xing, Ran Su, Gaotao Shi, ZhanShan Ma*, and Quan Zou*.

    CPPred-RF: a sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency.
    Journal of Proteome Research. 2017. 16(5), 2044-2053. (SCI, JCR-2, IF2015=4.173).
    [Server] | [PDF]

  13. Pengwei Xing, Ran Su, Fei Guo, and Leyi Wei*.

    Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine.
    Scientific Reports. 2017. 7, 46757. (IF2015=5.228).

  14. Leyi Wei, Jijun Tang, and Quan Zou*.
    SkipCPP-Pred: An Improved and Promising Method for Predicting Cell-Penetrating Peptides by Adaptive k-skip-n-gram Features.
    BMC Genomics. 2017. 18(Suppl 7):742. (SCI, JCR-2, IF2015=3.867).
    [Server] | [PDF]

  15. Leyi Wei, PengWei Xing, Gaotao Shi, Zhiliang Ji, and Quan Zou*. 
    Fast prediction of methylation sites using sequence-based feature selection technique.
    IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2017. (IF2015=1.609). DOI: 10.1109/TCBB.2017.2670558.

    [Server] | [PDF]

  16. Leyi Wei, PengWei Xing, Jijun Tang, and Quan Zou*. 
    PhosPred-RF: a novel sequence-based predictor for phosphorylation sites using sequential information only.
    IEEE Transactions on Nanobioscience. 2017. 16 (4): 240-247. (IF2015=1.969).
    [Server] | [PDF]

  17. Leyi Wei, Jijun Tang, and Quan Zou*.
    Local-DPP: An Improved DNA-binding Protein Prediction Method by Exploring Local Evolutionary Information. 
    Information Sciences. 2017. 384:135-144. (SCI, JCR-2,IF2015=3.364)
    .
    [Server] | [PDF]

Projects

Academic activities

My students at TJU

 

Last Update: 2020/3/11

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