代绍兴(Shaoxing Dai)

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，讲师

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

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

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. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. 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.
12. 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.
13. 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.
14. 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.
15. 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.
16. 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).
17. 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).
18. 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).
19. 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.
20. 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.
21. 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.
22. 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.
23. 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.

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.