• 代绍兴(Shaoxing Dai)

      博士、研究人员

      副教授

      Associate Professor

      一、受教育及工作经历 Education andAcademic Positions

      • 2004.09-2008.06：兰州大学，生命科学学院，生物科学，理学学士
      • 2008.09-2013.06：中国科学技术大学，生物化学与分子生物学，理学博士
      • 2013.6-2018.12：中国科学院昆明动物研究所，助理研究员
      • 2018.12-至今：昆明理工大学灵长类转化医学研究院，副教授

       

      • 2008.09-2013.06: School of Life Sciences, University of Science and Technology of China (USTC), Ph. D. in Biochemistry and Molecular Biology
      • 2004.09-2008.06: School of Life Sciences, Lanzhou University, B. S. in Biological Science
      • 2013.6-2018.12: Assistant professor, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences
      • 2018.12-Now: lecturer, Institute of Primate Translational Medicine, Kunming University of Science and Technology

      二、主要研究方向 Research interests

      1. 通过整合严重疾病中的多组学数据发掘和鉴定治疗靶标(系统生物学)
      2. 对治疗靶点及其药物结合口袋进行三维结构分析和可视化(结构生物信息学)
      3. 筛选和设计能够靶向和调控治疗靶点的先导化合物(药物发现)
      4. 机器学习和深度学习在转化医学中的运用

      I mainly focus on the application of bioinformatics and machine learning in target identification and drug discovery by integrating multi-omics data.

      1. Identification of therapeutic targetby integrating multi-omics data in serious diseases (System biology)
      2. Structural analysis of thetherapeutic target and its drug-binding site (Structuralbioinformatics)
      3. Screening and design the lead compounds that modulate the target (Drug discovery)
      4. Application of Machine learning and deep learning

      三、科研领域描述 Research Field

      专注于利用生物信息学和机器学习等工具，整合疾病的多组学数据，来进行疾病的靶点识别和药物发现

       

      Mainly focus on the application of bioinformatics and machine learning in target identification and drug discovery by integrating multi-omics data.

      四、承担科研项目情况 Research funding

      1. 国家自然科学基金-青年科学基金项目，2015-2017，24万，项目名称：抗HIV新靶标的生物信息学发掘和实验验证，主持
      2. 国家自然科学基金-青年科学基金项目，2015-2017，20万，项目名称：基于"标志物—靶标—药物"复合网络构建肿瘤个体化治疗模型的研究，主要参与
      3. 企业合作技术开发横向项目，2016-2021，100万，项目名称：神经药物信息学分析，主要参与
      1. 2015-2017: "Identifying new anti-HIV targets using bioinformatics and experimental verification", National Natural Science Foundation of China (Grant No. 31401142), PI
      2. 2015-2017: Constructing personalized cancer therapeutic model based on thecomposite network of "Biomarkers-Targets-Drugs", National Natural Science Foundation of China (Grant No. 31401137), principal member.
      3. 2016-2021: Bioinformatics analysis of psychiatric medications, Enterprise cooperative technology development project, principal member

      五、代表性论文 Publications

      1. Wen-Xing Li*, Gong-Hua Li*, Xin Tong, Peng-Peng Yang, Jing-Fei Huang#, Lin Xu#, Shao-Xing Dai#.Systematic metabolic analysis of potential target, therapeutic drug, diagnostic method and animal model applicability in three neurodegenerative diseases.Aging. 2020; 12:9882-9914. https://doi.org/10.18632/aging.103253.

      2. Li Bing-Xiang#, Zhang Han#, Liu Yubin#, Li Ya#, Zheng Jun-Juan, Li Wen-Xing, Feng Kai, Sun Ming*, Dai Shao-Xing*. Novel pathways of HIV latency reactivation revealed by integrated analysis of transcriptome and target profile of bryostatin. Scientific Reports. 2020, 10(1): 3511.

      3. Zhou X, Li G, An S, et al. A new method of identifying glioblastoma subtypes and creation of corresponding animal models[J]. Oncogene, 2018, 37(35): 4781.
      4. Zheng J J, Dai S X*, et al. Low expression of aging-related NRXN3 is associated with Alzheimer disease: A systematic review and meta-analysis[J]. Medicine, 2018, 97(28): e11343.
      5. Chen B W, Dai S X*, et al. A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants[J]. PeerJ, 2018, 6: e4756.
      6. Dai S X, Li W X, Li H J, et al. Anti-HIV activity prediction and enrichment identify novel human targets for Anti-HIV therapy[J]. bioRxiv, 2017: 159236.
      7. Dai S X, Chen H, Li W X, et al. Efficient repositioning of approved drugs as anti-HIV agents using Anti-HIV-Predictor[J]. bioRxiv, 2017: 087445.
      8. Li W X, Qi F, Liu J Q, Li G H, Dai S X, et al. Different impairment of immune and inflammation functions in short and long-term after ischemic stroke[J]. American Journal of Translational Research, 2017, 9(2): 736.
      9. Li W X, He K, Tang L, Dai S X, et al. Comprehensive tissue-specific gene set enrichment analysis and transcription factor analysis of breast cancer by integrating 14 gene expression datasets[J]. Oncotarget, 2017, 8(4): 6775.
      10. Li W X, Cheng F, Zhang A J, Dai S X,et al. Folate Deficiency and Gene Polymorphisms of MTHFR, MTR and MTRR Elevate the Hyperhomocysteinemia Risk[J]. Clinical laboratory, 2017, 63(3): 523-533.
      11. Wang Q, Li W X, Dai S X, et al. Meta-Analysis of Parkinson’s Disease and Alzheimer’s Disease Revealed Commonly Impaired Pathways and Dysregulation of NRF2-Dependent Genes[J]. Journal of Alzheimer's Disease, 2017;56(4):1525-1539.
      12. Liu J Q#, Dai S X#, Zheng J J, et al. The identification and molecular mechanism of anti-stroke traditional Chinese medicinal compounds[J]. Scientific Reports, 2017, 7.
      13. Li W X#, Dai S X#, Wang Q, et al. Integrated analysis of ischemic stroke datasets revealed sex and age difference in anti-stroke targets[J]. PeerJ, 2016, 4: e2470.
      14. Guo Y C, Zhang L, Dai S X, et al. Independent Evolution of Winner Traits without Whole Genome Duplication in Dekkera Yeasts[J]. PloS one, 2016, 11(5): e0155140.
      15. Dai S X, Li W X, Han F F, et al. In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database[J]. Scientific reports, 2016, 6.
      16. Dai S X, Li W X, Li G H, et al. Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin[J]. PeerJ, 2016, 4: e1791.
      17. Li W X#, Dai S X#, Liu J Q, et al. Integrated analysis of Alzheimer’s disease and schizophrenia dataset revealed different expression pattern in learning and memory[J]. Journal of Alzheimer's Disease, 2016, 51(2): 417-425.
      18. Han F, Li G, Dai S, et al. Genome-wide metabolic model to improve understanding of CD4+ T cell metabolism, immunometabolism and application in drug design[J]. Molecular BioSystems, 2016, 12(2): 431-443.
      19. Dai, S. X., Li, G. H., Gao, Y. D. & Huang, J. F. Pharmacophore-Map-Pick: A Method to Generate Pharmacophore Models for All Human GPCRs. Molecular Informatics (2015).
      20. Li, W.-X., Lv, W.-W., Dai, S.-X., Pan, M.-L. & Huang, J.-F. Joint associations of folate, homocysteine and MTHFR, MTR and MTRR gene polymorphisms with dyslipidemia in a Chinese hypertensive population: a cross-sectional study. Lipids in Health and Disease 14, 101 (2015).
      21. Li, W.-X#., Dai, S.-X#., Zheng, J.-J., Liu, J.-Q. & Huang, J.-F. Homocysteine Metabolism Gene Polymorphisms (MTHFR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) Jointly Elevate the Risk of Folate Deficiency. Nutrients 7, 6670-6687 (2015).
      22. Jiang H Y, Li G D, Dai S X, et al. Identification of PSEN1 mutations p. M233L and p. R352C in Han Chinese families with early-onset familial Alzheimer's disease[J]. Neurobiology of aging, 2015, 36(3): 1602. e3-1602. e6.
      23. Wang, R. R., Q. H. Yang, R. H. Luo, Y. M. Peng, S. X. Dai, X. J. Zhang, H. Chen, X. Q. Cui, Y. J. Liu, J. F. Huang, J. B. Chang, and Y. T. Zheng. "Azvudine, a Novel Nucleoside Reverse Transcriptase Inhibitor Showed Good Drug Combination Features and Better Inhibition on Drug-Resistant Strains Than Lamivudine in Vitro." PLoS One 9, no. 8 (2014): e105617.
      24. Zhang A D, Dai S X, Huang J F. Reconstruction and analysis of human kidney-specific metabolic network based on omics data[J]. BioMed research international, 2013, 2013.
      25. Li Z, Li T, Dai S, et al. New Insights into the Pharmacological Chaperone Activity of C2‐Substituted Glucoimidazoles for the Treatment of Gaucher Disease[J]. ChemBioChem, 2013, 14(10): 1239-1247.
      26. Dai S X, Zhang A D, Huang J F. Evolution, expansion and expression of the Kunitz/BPTI gene family associated with long-term blood feeding in Ixodes Scapularis[J]. BMC evolutionary biology, 2012, 12(1): 4.

      六、申请专利 Patents

      1. 代绍兴, 黄京飞, 陈欢,郑永唐, 李功华, 李文兴. 达巴万星在制备治疗艾滋病的药物中的应用. CN106668833A. 2017.
      2. 代绍兴, 黄京飞, 陈欢,郑永唐, 李功华, 李文兴. 西曲瑞克在制备治疗艾滋病的药物中的应用. CN107007814A. 2017.
      3. 代绍兴, 黄京飞, 陈欢,郑永唐, 李功华, 李文兴. 蒽环类化合物在制备治疗艾滋病的药物中的应用. CN107041891A. 2017.
      4.  李功华, 黄京飞, 李文兴, 代绍兴, 唐承薇, 童欢. 肝硬化早期小分子标志物及其应用. CN108572251A. 2018.
      5. 李文兴, 李功华, 黄京飞, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的结肠癌个性化预后评估方法. CN108320806A. 2018.
      6.  李文兴, 李功华, 黄京飞, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的肺腺癌个性化预后评估方法. CN108363907A. 2018.
      7.  黄京飞, 李文兴, 李功华, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的胃癌个性化预后评估方法. CN108470111A. 2018.
      8.  李文兴, 李功华, 黄京飞, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的宫颈癌个性化预后评估方法. CN108611416A. 2018.
      9. 李文兴, 李功华, 黄京飞, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的肝癌个性化预后评估方法. CN108630317A. 2018.
      10.  李功华, 李文兴, 黄京飞, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的胰腺癌个性化预后评估方法. CN108648826A. 2018.
      11.  李文兴, 李功华, 黄京飞, 赵旭东, 代绍兴. 一种基于多基因表达特征谱的肾透明细胞癌个性化预后评估方法. CN108647493A. 2018.
      12. 赵旭东, 李文兴, 李功华, 黄京飞, 代绍兴. 一种基于多基因表达特征谱的胶质母细胞瘤个性化预后评估方法. CN108733980A. 2018.
       
      1. CN106668833A, Application of Dalbavancin in preparation of medicine for curing AIDS. (Invention Patent under substantive review)
      2. CN107007814A, Application of Cetrorelix in preparation of medicine for curing AIDS. (Invention Patent under substantive review)
      3. CN107041891A, Application of Anthracycline compounds in preparation of medicine for curing AIDS. (Invention Patent under substantive review)
      4. CN108320806A, A personalized prognostic evaluation method for colon cancer based on multi-gene expression profile
      5. CN108363907A, A personalized prognostic evaluation method for lung adenocarcinoma based on multi-gene expression profile
      6. 201810548561.3, Small molecular biomarkers of early liver cirrhosis and their application

      七、研究人员

      白冰

      博士，讲师

      主要研究方向：

      1. 灵长类多组学数据库建构
      2. 发育障碍类疾病病因研究  

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