English Version


  • 吕志彬，特聘副研究员，四川大学生物医学工程学院
  • 欢迎有志于利用人工智能解决生物、医学、材料的学生报考
  • 保研生和本科生联系时，请发详细简历到学术邮箱，邮件命名好，不然会被自动处理掉
    		•


    研究方向：

  • 生物序列的人工智能分析技术
  • 药物分子的人工智能开发技术
  • 第1性原理计算
    		•

    教育背景:

  • 电子科技大学基础前沿院计算机博士后（导师：邹权教授（杰青））
  • 北京大学化学院高分子专业博士（导师：邹德春（杰青/973首席））
  • 厦门大学化学院材料专业学士（嘉庚奖学金获得者）
    		•

    主持项目：

    国家自然科学基金面上项目基金    治疗肽BERT表示学习机制的研究（在研）
    国家自然科学基金青年基金    基于多联碱基的人类转录组的数据不平衡问题研究 (已结题)
    中国博士后基金面上项目    基于蛋白质统一表示学习的蛋白亚细胞定位 (已结题)

    学术兼职：

    多个杂志客座编辑

    代表论文：

    1. Li Honghao, Jiang Liangzhen, Yang Kaixiang, Shang Shulin, Li Mingxin, Lv Zhibin: iNP_ESM: Neuropeptide Identification Based on Evolutionary Scale Modeling and Unified Representation Embedding Features. International Journal Of Molecular Sciences 2024, 25(13):7049.
    2. Jiang Jici, Pei Hongdi, Li Jiayu, Li Mingxin, Zou Quan, Lv Zhibin: FEOpti-ACVP: identification of novel anti-coronavirus peptide sequences based on feature engineering and optimization. Briefings In Bioinformatics 2024, 25(2):bbae037.
    3. Pei Hongdi, Li Jiayu, Ma Shuhan, Jiang Jici, Li Mingxin, Zou Quan, Lv Zhibin: Identification of Thermophilic Proteins Based on Sequence-Based Bidirectional Representations from Transformer-Embedding Features. Applied Sciences-Basel 2023, 13(5):2858.
    4. Lv Zhibin, Li Mingxin, Wang Yansu, Zou Quan: Editorial: Machine learning for biological sequence analysis. Frontiers In Genetics 2023, 14:1150688.
    5. Li Jiayu, Ma Shuhan, Pei Hongdi, Jiang Jici, Zou Quan, Lv Zhibin: Review of T cell proliferation regulatory factors in treatment and prognostic prediction for solid tumors. Heliyon 2023, 9(11):e21329.
    6. Li Jiayu, Jiang Jici, Pei Hongdi, Lv Zhibin: A Stacking Machine Learning Method for IL-10-Induced Peptide Sequence Recognition Based on Unified Deep Representation Learning. Applied Sciences-Basel 2023, 13(16):9346.
    7. Jiang Jici, Li Jiayu, Li Junxian, Pei Hongdi, Li Mingxin, Zou Quan, Lv Zhibin: A Machine Learning Method to Identify Umami Peptide Sequences by Using Multiplicative LSTM Embedded Features. Foods 2023, 12(7):1498.
    8. Deng Yiting, Ma Shuhan, Li Jiayu, Zheng Bowen, Lv Zhibin: Using the Random Forest for Identifying Key Physicochemical Properties of Amino Acids to Discriminate Anticancer and Non-Anticancer Peptides. International Journal Of Molecular Sciences 2023, 24(13):10854.
    9. Zhao Qian, Ma Jiaqi, Wang Yu, Xie Fang, Lv Zhibin, Xu Yaoqun, Shi Hua, Han Ke: Mul-SNO: A Novel Prediction Tool for S-Nitrosylation Sites Based on Deep Learning Methods. Ieee Journal Of Biomedical And Health Informatics 2022, 26(5):2379-2387.
    10. Li Mingxin, Fan Yu, Zhang Yiting, Lv Zhibin: Using Sequence Similarity Based on CKSNP Features and a Graph Neural Network Model to Identify miRNA-Disease Associations. Genes 2022, 13(10):1759.
    11. Jiang Liangzhen, Liu Changying, Fan Yu, Wu Qi, Ye Xueling, Li Qiang, Wan Yan, Sun Yanxia, Zou Liang, Xiang Dabing, Lv Zhibin: Dynamic transcriptome analysis suggests the key genes regulating seed development and filling in Tartary buckwheat (Fagopyrum tataricum Garetn.). Frontiers In Genetics 2022, 13:990412.
    12. Jiang Liangzhen, Jiang Jici, Wang Xiao, Zhang Yin, Zheng Bowen, Liu Shuqi, Zhang Yiting, Liu Changying, Wan Yan, Xiang Dabing, Lv Zhibin: IUP-BERT: Identification of Umami Peptides Based on BERT Features. Foods 2022, 11(22):3742.
    13. Jiang Jici, Lin Xinxu, Jiang Yueqi, Jiang Liangzhen, Lv Zhibin: Identify Bitter Peptides by Using Deep Representation Learning Features. International Journal Of Molecular Sciences 2022, 23(14):7877.
    14. Yan Ni, Lv Zhibin, Hong Wenjing, Xu Xue: Editorial: Feature Representation and Learning Methods With Applications in Protein Secondary Structure. Frontiers In Bioengineering And Biotechnology 2021, 9:748722.
    15. Lv Zhibin, Ding Hui, Wang Lei, Zou Quan: A Convolutional Neural Network Using Dinucleotide One-hot Encoder for identifying DNA N6-Methyladenine Sites in the Rice Genome. Neurocomputing 2021, 422:214-221.
    16. Lv Zhibin, Cui Feifei, Zou Quan, Zhang Lichao, Xu Lei: Anticancer peptides prediction with deep representation learning features. Briefings In Bioinformatics 2021, 22(5):bbab008.
    17. Lv Zhibin, Zhang Jun, Ding Hui, Zou Quan: RF-PseU: A Random Forest Predictor for RNA Pseudouridine Sites. Frontiers In Bioengineering And Biotechnology 2020, 8:134.
    18. Lv Zhibin, Wang Pingping, Zou Quan, Jiang Qinghua: Identification of sub-Golgi protein localization by use of deep representation learning features. Bioinformatics 2020, 36(24):5600-5609.
    19. Lv Zhibin, Wang Donghua, Ding Hui, Zhong Bineng, Xu Lei: Escherichia Coli DNA N-4-Methycytosine Site Prediction Accuracy Improved by Light Gradient Boosting Machine Feature Selection Technology. Ieee Access 2020, 8:14851-14859.
    20. Lv Zhibin, Jin Shunshan, Ding Hui, Zou Quan: A Random Forest Sub-Golgi Protein Classifier Optimized via Dipeptide and Amino Acid Composition Features. Frontiers In Bioengineering And Biotechnology 2019, 7:215.
    21. Lv Zhibin, Ao Chunyan, Zou Quan: Protein Function Prediction: From Traditional Classifier to Deep Learning. Proteomics 2019, 19(14):1900119.
    22. Liang Xin, Zhu Wen, Lv Zhibin, Zou Quan: Molecular Computing and Bioinformatics. Molecules 2019, 24(13):2358.

    所获奖励：

  • 教育部自然科学奖二等奖（排名第8）

    •

    培养学生：

  • 四川大学

    •

    教学课程：

  • 本科：医学统计学、生物信息学、数据库与信息管理、医学信息系统、本科毕业论文、信息论（筹）
  • 硕博：生物医学信息与临床

    •

    本科生大创和比赛：

  • 国家级1个，省级2个；四川省生物医学工程大赛二等奖、三等奖

    •

    联系方式：

  • Email: 姓名全称(a)pku.edu.cn(为防止垃圾邮件，请把(a)换成@)

    •

    最后修改时间：2024.9.28
    蜀ICP备19040033号