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

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
4. 云南省基础研究计划-面上项目，2019-2022，10万，项目名称：利用机器学习发掘新型低毒抗细菌化合物及其实验验证，主持
5. 云南省高层次科技人才及创新团队选拔专项，2020-2025，12万，项目名称：技术创新人才培养对象项目代绍兴，主持
6. 国家自然科学基金——地区科学基金项目，2022-2025，34万，项目名称：基于机器学习和异体住囊虫模型的抗衰老化合物筛选及其机制研究，主持
7. 云南省技术创新人才培养对象项目，2022-2025，12万，项目名称：云南省技术创新人才培养对象项目，主持
8. 中央引导地方项目，2022-2023，40万，项目名称：联合人工智能和动物模型进行抗衰老化合物筛选研究，主持
9. 国家自然科学地区项目，2022-2025，34万，项目名称：基于机器学习和异体住囊虫模型的抗衰老化合物筛选及其机制研究

1. Yu Kang#, Shaoxing Dai#, Yuqiang Zeng#, Fang Wang#, Pengpeng Yang, Zhaohui Yang, Youwei Pu1,3, Zifan Li, Xinglong Chen1, Baohong Tian, Wei Si, Weizhi Ji*, Yuyu Niu*. Cloning and base editing of GFP transgenic rhesus monkey and off-target analysis. Science Advances. 2022.7 8(29)：1-11 [IF: 14.957]
2. Tong L.; Dai S. X.; Kong D. J.; Yang P. P.; Tong X.; Tong X. R.; Bi X. X.; Su Y.; Zhao Y. Q.; Liu Z. C.; The genome of medicinal leech (Whitmania pigra) and comparative genomic study for exploration of bioactive ingredients, BMC Genomics, 2022, 23(1): 76.
3. Li W. X.; Tong X.; Yang P. P.; Zheng Y.; Liang J. H.; Li G. H.; Liu D. H.; Guan D. G.; Dai S. X.; Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods, Aging, 2022, 14(3): 1448-1472.
4. Yang H.; Yang S.; Fan F.; Li Y.; Dai S.; Zhou X.; Steiner C. C.; Coppedge B.; Roos C.; Cai X.; Irwin D. M.; Shi P.; A New World Monkey Resembles Human in Bitter Taste Receptor Evolution and Function via a Single Parallel Amino Acid Substitution, Mol Biol Evol, 2021, 38(12): 5472-5479.
5. Xin Tong#，Wen-Xing Li#，Jihao Liang，Yang Zheng，Shao-xing Dai*.Two different aging paths in human blood revealed by integrated analysis of gene Expression, mutation and alternative splicing.Gene. 2022, 146501.2022.4.[IF: 3.688]
6. Tan Tao^#; Wu Jun^#; Si Chenyang^#; Dai Shaoxing^#; Zhang Youyue; Sun Nianqin; Zhang E; Shao Honglian; Si Wei; Yang Pengpeng; Hong Wang; Zhenzhen Chen; Ran Zhu; Yu Kang; Reyna Hernandez-Benitez; Llanos Martinez Martinez; Estrella Nuñez Delicado; W Travis Berggren; May Schwarz; Zongyong Ai; Tianqing Li; Concepcion Rodriguez Esteban; Weizhi Ji*; Yuyu Niu*; Juan Carlos Izpisua Belmonte*; Chimeric contribution of human extended pluripotent stem cells to monkey embryos ex vivo, Cell, 2021, 184(8): 2020-2032. e2014.
7. Liu Dahai^#; Dai Shao-Xing^#; He Kan; Li Gong-Hua; Liu Justin; Liu Leyna G; Huang Jing-Fei; Xu Lin; Li Wen-Xing; Identification of hub ubiquitin ligase genes affecting Alzheimer’s disease by analyzing transcriptome data from multiple brain regions, Science Progress, 2021, 104(1): 00368504211001146.
8. Li Wen-Xing^#; Dai Shao-Xing^#; An San-Qi^#; Sun Tingting^#; Liu Justin; Wang Jun; Liu Leyna G; Xun Yang; Yang Hua; Fan Li-Xia; Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma, Aging, 2021, 13
9. Wang Fang; Zhang Weiqi; Yang Qiaoyan; Kang Yu; Fan Yanling; Wei Jingkuan; Liu Zunpeng; Dai Shaoxing; Li Hao; Li Zifan; Generation of a Hutchinson–Gilford progeria syndrome monkey model by base editing, Protein & cell, 2020, 11(11): 809-824.
10. Li Wen-Xing; Li Gong-Hua; Tong Xin; Yang Peng-Peng; Huang Jing-Fei*; Xu Lin*; Dai Shao-Xing*; Systematic metabolic analysis of potential target, therapeutic drug, diagnostic method and animal model applicability in three neurodegenerative diseases, Aging, 2020, 12(10): 9882.
11. Li Gong-Hua; Dai Shaoxing; Han Feifei; Li Wenxin; Huang Jingfei; Xiao Wenzhong; FastMM: an efficient toolbox for personalized constraint-based metabolic modeling, BMC Bioinformatics, 2020, 21(1): 1-7.
12. 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): 1-12.
13. Liu Jia-Qian; Li Wen-Xing; Zheng Jun-Juan; Tian Qing-Nan; Huang Jing-Fei*; Dai Shao-Xing*; Gain and loss events in the evolution of the apolipoprotein family in vertebrata, BMC evolutionary biology, 2019, 19(1): 1-10.
14. Li Huijuan; Zhou Dong-Sheng; Chang Hong; Wang Lu; Liu Weipeng; Dai Shao-Xing; Zhang Chen; Cai Jun; Liu Weiqing; Li Xingxing; Interactome Analyses implicated CAMK2A in the genetic predisposition and pharmacological mechanism of Bipolar Disorder, Journal of psychiatric research, 2019, 115(165-175).
15. Zhou Xia; Li Gonghua; An Sanqi; Li Wen-Xing; Yang Huihui; Guo Yicheng; Dai Zhi; Dai Shaoxing; Zheng Junjuan; Huang Jingfei; A new method of identifying glioblastoma subtypes and creation of corresponding animal models, Oncogene, 2018, 37(35): 4781-4791.
16. Zheng Jun-Juan; Li Wen-Xing; Liu Jia-Qian; Guo Yi-Cheng; Wang Qian; Li Gong-Hua*Dai Shao-Xing*; Huang Jing-Fei*; Low expression of aging-related NRXN3 is associated with Alzheimer disease: A systematic review and meta-analysis, Medicine, 2018, 97(28):
17. Li Hui‑Juan; Li Wen‑Xing; Dai Shao‑Xing; Guo Yi‑Cheng; Zheng Jun‑Juan; Liu Jia‑Qian; Wang Qian; Chen Bi‑Wen; Li Gong‑Hua; Huang Jing‑Fei; Identification of metabolism-associated genes and pathways involved in different stages of clear cell renal cell carcinoma, Oncology Letters, 2018, 15(2): 2316-2322.
18. Chen Bi-Wen; Li Wen-Xing; Wang Guang-Hui; Li Gong-Hua; Liu Jia-Qian; Zheng Jun-Juan; Wang Qian; Li Hui-Juan; Dai Shao-Xing*; Huang Jing-Fei*; A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants, PeerJ, 2018, 6(e4756.
19. Wang Qian; Li Wen-Xing; Dai Shao-Xing; Guo Yi-Cheng; Han Fei-Fei; Zheng Jun-Juan; Li Gong-Hua; Huang Jing-Fei; Meta-Analysis of Parkinson’s Disease and Alzheimer’s Disease Revealed Commonly Impaired Pathways and Dysregulation of NRF2-Dependent Genes, Journal of Alzheimer's Disease, 2017, 56(4): 1525-1539.
20. Liu Jia-Qian^#; Dai Shao-Xing^#; Zheng Jun-Juan; Guo Yi-Cheng; Li Wen-Xing; Li Gong-Hua; Huang Jing-Fei; The identification and molecular mechanism of anti-stroke traditional Chinese medicinal compounds, Scientific Reports, 2017, 7(41406).
21. Li Wen-Xing; Qi Fei; Liu Jia-Qian; Li Gong-Hua; Dai Shao-Xing; Zhang Tao; Cheng Fei; Liu Dahai; Zheng Song Guo; Different impairment of immune and inflammation functions in short and long-term after ischemic stroke, American Journal of Translational Research, 2017, 9(2): 736.
22. Li Wen-Xing; He Kan; Tang Ling; Dai Shao-Xing; Li Gong-Hua; Lv Wen-Wen; Guo Yi-Cheng; An San-Qi; Wu Guo-Ying; Liu Dahai; Comprehensive tissue-specific gene set enrichment analysis and transcription factor analysis of breast cancer by integrating 14 gene expression datasets, Oncotarget, 2017, 8(4): 6775.
23. Li Wen-Xing; Cheng Fei; Zhang A-Jie; Dai Shao-Xing; Li Gong-Hua; Lv Wen-Wen; Zhou Tao; Zhang Qiang; Zhang Hong; Zhang Tao; Folate deficiency and gene polymorphisms of MTHFR, MTR and MTRR elevate the hyperhomocysteinemia risk, Clin Lab, 2017, 63(3): 523-533.
24. Li Wen-Xing^#; Dai Shao-Xing^#; Wang Qian; Guo Yi-Cheng; Hong Yi; Zheng Jun-Juan; Liu Jia-Qian; Liu Dahai; Li Gong-Hua; Huang Jing-Fei; Integrated analysis of ischemic stroke datasets revealed sex and age difference in anti-stroke targets, PeerJ, 2016, 4(e2470).
25. Li Wen-Xing^#; Dai Shao-Xing^#; Liu Jia-Qian; Wang Qian; Li Gong-Hua; Huang Jing-Fei; Integrated Analysis of Alzheimer’s Disease and Schizophrenia Dataset Revealed Different Expression Pattern in Learning and Memory, Journal of Alzheimer's Disease, 2016, 51(2): 417-425.
26. Han Feifei; Li Gonghua; Dai Shaoxing; Huang Jingfei; Genome-wide metabolic model to improve understanding of CD4+ T cell metabolism, immunometabolism and application in drug design, Molecular BioSystems, 2016, 12(2): 431-443.
27. Guo Yi-Cheng; Zhang Lin; Dai Shao-Xing; Li Wen-Xing; Zheng Jun-Juan; Li Gong-Hua; Huang Jing-Fei; Independent evolution of winner traits without whole genome duplication in Dekkera yeasts, PLOS ONE, 2016, 11(5): e0155140.
28. Dai Shao-Xing; Li Wen-Xing; Li Gong-Hua; Huang Jing-Fei; Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin, PeerJ, 2016, 4(e1791).
29. Dai Shao-Xing; Li Wen-Xing; Han Fei-Fei; Guo Yi-Cheng; Zheng Jun-Juan; Liu Jia-Qian; Wang Qian; Gao Yue-Dong; Li Gong-Hua; Huang Jing-Fei; In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database, Scientific Reports, 2016, 6(1): 1-11.
30. Dai Shao-Xing; Li Gong-Hua; Gao Yue-Dong; Huang Jing-Fei; Pharmacophore-Map-Pick: A Method to Generate Pharmacophore Models for All Human GPCRs, Molecular Informatics, 2016, 35(2): 81-91.
31. Li Wen-Xing; Lv Wen-Wen; Dai Shao-Xing; Pan Ming-Luo; Huang Jing-Fei; 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, 2015, 14(1): 1.
32. Li Wen-Xing^#; Dai Shao-Xing^#; Zheng Jun-Juan; Liu Jia-Qian; Huang Jing-Fei; Homocysteine Metabolism Gene Polymorphisms (MTHFR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) Jointly Elevate the Risk of Folate Deficiency, Nutrients, 2015, 7(8): 6670-6687.
33. Jiang Hong-Yan; Li Guo-Dong; Dai Shao-Xing; Bi Rui; Zhang Deng-Feng; Li Zong-Fang; Xu Xiu-Feng; Zhou Tai-Cheng; Yu Li; Yao Yong-Gang; Identification of PSEN1 mutations p. M233L and p. R352C in Han Chinese families with early-onset familial Alzheimer's disease, Neurobiology of aging, 2015, 36(3): 1602. e1603-1602. e1606.
34. Wang Rui-Rui; Yang Qing-Hua; Luo Rong-Hua; Peng You-Mei; Dai Shao-Xing; Zhang Xing-Jie; Chen Huan; Cui Xue-Qing; Liu Ya-Juan; Huang Jing-Fei; 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, 2014, 9(8): e105617.
35. Zhang Ai-Di; Dai Shao-Xing; Huang Jing-Fei; Reconstruction and analysis of human kidney-specific metabolic network based on omics data, BioMed research international, 2013
36. Li Zhonghua; Li Tiehai; Dai Shaoxing; Xie Xiaoli; Ma Xiaofeng; Zhao Wei; Zhang Weimin; Li Jing; Wang Peng George; New Insights into the Pharmacological Chaperone Activity of C2-Substituted Glucoimidazoles for the Treatment of Gaucher Disease, ChemBioChem, 2013, 14(10): 1239-1247.
37. Dai Shao-Xing; Zhang Ai-Di; Huang Jing-Fei; Evolution, expansion and expression of the Kunitz/BPTI gene family associated with long-term blood feeding in Ixodes Scapularis, BMC evolutionary biology, 2012, 12(1): 1-16.

论文网站(动态更新) https://scholar.google.com/citations?user=d4cYz1YAAAAJ

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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）
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.（已授权）

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