| 姓名：杜红丽 职称：教授、博士生导师、硕士生导师 研究方向：遗传与生物信息学、多组学整合技术、泛肿瘤分子机制、肿瘤和传染病药物研发 电子邮箱：hldu@scut.edu.cn 办公地点：B6-413 办公电话：02039380667 |
博士生：生化与分子生物学
硕士生：生化与分子生物学
专业学位硕士：生物工程、药学
1995.9－1999.7：华南农业大学 畜牧 学士
1999.9－2002.7：华南农业大学 动物遗传育种 硕士
2002.9－2005.7：华南农业大学 动物遗传育种 博士
2006.1－2009.8 华南理工大学 讲师
2006.5－2006.8 中国医学科学院生物技术研究所进修
2009.9－2015.8 华南理工大学 副教授
2015.9－至今 华南理工大学 教授
2013.1-2015.12 期间曾经到斯坦福大学基因组中心、UC Davis等机构进行合作交流。
本科生教学：基因组学、系统生物学
研究生教学：分子遗传学、分子生物学
国家重点研发计划项目负责人，国内较早从事基因组的研究人员之一。作为2009年华工华大第一届基因组科学创新班班主任，借助华南理工大学与华大基因联合培养硕、博士的契机，已培养出高通量测序研究和应用型人才超80人，他们在华大基因、金域检验、达安基因等基因检测龙头企业发挥中流砥柱的作用。迄今主持或参与国家重点研发、重大专项和科技支撑等各类项目20余项；在Nat Biotechnol、Frontiers in Immunology、Computational and Structural Biotechnology Journal、Cancers、Front Psychol等国际著名杂志发表SCI论文50余篇，总影响因子180，总引逾1800 次；申请发明专利10项，授权4项，获软件著作权16项，获省部级科技进步二等奖1项。Briefings in Bioinformatics、eBioMedicine、Theranostics、Molecular Therapy - Nucleic Acids、Computational and Structural Biotechnology Journal、Human Genetics、Frontiers in Immunology、Frontiers in Oncology、BMC Cancer、Frontiers in Genetics、International Journal of Infectious Diseases 等杂志评委。
科研兴趣：
（1）基于人工智能的多组学大数据分析技术开发与应用；
（2）基于组织、单细胞和时空多组学大数据以及系统生命调控的肿瘤和传染病机制揭示和治疗靶标鉴定；
（3）基于深度学习的高通量小分子药物筛选；
（4）基于组学的肿瘤早期诊断和精准用药诊断方法和工具开发及应用。
科研项目：
[1]主持国家重点研发项目：医学生命组学数据质量控制关键技术研发与应用（2018-2021）
[2]主持广东省重点领域项目：多组学整合技术研发及标准化组学数据质量控制技术的推广应用（2019-2022）
[3] 参与十二五重大专项（副组长）：人类重大疾病灵长类动物模型资源平台的建设（2011-2013）
[4] 主持广东省科技计划项目：食蟹猴2型糖尿病模型构建和评价体系的建立和完善（2012-2013）
[5] 主持国家自然科学基金：食蟹猴2型糖尿病模型发病进程的分子机制研究（2014）
[6] 参与科技支撑项目：灵长类动物人类重大疾病模型的研究与示范（2014-2016）
[7] 参与科技支撑项目：实验动物感染病原的MFIA、PCR-HRM、基因芯片检测诊断和遗传质量SNP检测的新技术方法研究和应用（2015-2017）
1.Xi B, Meng Y, Jiang D, Bai Y, Chen Z, Qu Y, Li S, Wei J,Huang L, Du H*. Analyses of Long-Term Epidemic Trends and Evolution Characteristics of Haplotype Subtypes Reveal the Dynamic Selection on SARS-CoV-2. Viruses . 2022 Feb 23;14,454.
2.Wei J, Hu M and Du H*. Improving Cancer Immunotherapy: Exploring and Targeting Metabolism in Hypoxia Microenvironment. Front Immunol. 2022 Feb 24;13:845923.
3.Bai Yunmeng, Meiling Hu, Zixi Chen, Jinfen Wei*, Hongli Du*. Single-Cell Transcriptome Analysis Reveals RGS1 as a New Marker and Promoting Factor for T-Cell Exhaustion in Multiple Cancers. Front Immunol, 2021,12:5153. doi: 10.3389/fimmu.2021.767070
4.Jinfen Wei, Zixi Chen, Meiling Hu, Ziqing He, Dawei Jiang, Jie Long, Hongli Du*. Characterizing Intercellular Communication of Pan-Cancer Reveals SPP1+ Tumor-Associated Macrophage Expanded in Hypoxia and Promoting Cancer Malignancy Through Single-Cell RNA-Seq Data. Front Cell Dev Biol, 2021(9):2721.
5.Xi B, Chen Z, Li S, Liu W, Jiang D, Bai Y, Qu Y, Lon JR, Huang L, Du H*. AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus. Comput Struct Biotechnol J. 2021;19:5029-5038. doi: 10.1016/j.csbj.2021.09.002
6.Guanda Huang, Haibo Zhang, Yimo Qu, Kaitang Huang, Xiaocheng Gong, Jinfen Wei*, Hongli Du*. ARMT: An automatic RNA-seq data mining tool based on comprehensive and integrative analysis in cancer research. Comput Struct Biotechnol J. 2021(19): 4426-4434.
7.Huang K, Hu M, Chen J, Wei J, Qin J, Lin S*, Du H*. Multi-Omics Perspective Reveals the Different Patterns of Tumor Immune Microenvironment Based on Programmed Death Ligand 1 (PD-L1) Expression and Predictor of Responses to Immune Checkpoint Blockade across Pan-Cancer. Int J Mol Sci 2021, 22, 5158.
8.Xi B, Jiang D, Li S, Lon JR, Bai Y, Lin S, Hu M, Meng Y, Qu Y, Huang Y, Liu W, Huang L, Du H*. AutoVEM: An automated tool to real-time monitor epidemic trends and key mutations in SARS-CoV-2 evolution. Comput Struct Biotechnol J. 2021;19:1976-1985. doi: 10.1016/j.csbj.2021.04.002.
9.Bai Y, Jiang D, Lon JR, Chen X, Hu M, Lin S, Chen Z, Wang X, Meng Y*, Du H*. Comprehensive evolution and molecular characteristics of a large number of SARS-CoV-2 genomes reveal its epidemic trends. Int J Infect Dis. 2020 Nov;100:164-173. doi: 10.1016/j.ijid.2020.08.066.
10.Lon JR, Bai Y, Zhong B, Cai F, Du H*. Prediction and evolution of B cell epitopes of surface protein in SARS-CoV-2. Virol J. 2020 Oct 29;17(1):165. doi: 10.1186/s12985-020-01437-4.
11.Wei J, Hu M, Huang K, Lin S, Du H*. Roles of Proteoglycans and Glycosaminoglycans in Cancer Development and Progression. Int J Mol Sci 2020, 21(17), 5983; https://doi.org/10.3390/ijms21175983
12.Wei J, Huang K, Chen Z, Hu M, Bai Y, Lin S, Du H*. Characterization of Glycolysis-Associated Molecules in the Tumor Microenvironment Revealed by Pan-Cancer Tissues and Lung Cancer Single Cell Data. Cancers (Basel). 2020 Jul 4;12(7):E1788. doi: 10.3390/cancers12071788.
13.Wang J, Li S, Lin S, Fu S, Qiu L, Ding K, Liang K, Du H*. B-cell lymphoma 2 family genes show a molecular pattern of spatiotemporal heterogeneity in gynaecologic and breast cancer. Cell Prolif. 2020 Jun;53(6):e12826. doi: 10.1111/cpr.12826. Epub 2020 May 17.
14.Chen Z, Yuan Y, Chen X, Chen J, Lin S, Li X, Du H*. Systematic comparison of somatic variant calling performance among different sequencing depth and mutation frequency. Sci Rep. 2020 Feb 26;10(1):3501. doi: 10.1038/s41598-020-60559-5.
15.Zhang W, Bai Y, Chen Z, Li X, Fu S, Huang L, Lin S*, Du H*. Comprehensive analysis of long non-coding RNAs and mRNAs in skeletal muscle of diabetic Goto-Kakizaki rats during the early stage of type 2 diabetes. PeerJ. 2020 Feb 12;8:e8548. doi: 10.7717/peerj.8548.
16.Fu S, Meng Y, Lin S, Zhang W, He Y, Huang L, Du H*. Transcriptomic responses of hypothalamus to acute exercise in type 2 diabetic Goto-Kakizaki rats. Peer J. 2019 Sep 24;7:e7743. doi: 10.7717/peerj.7743.
17.He Y, Li X, Meng Y, Fu S, Cui Y, Shi Y*, Du H*. A prognostic 11 long noncoding RNA expression signature for breast invasive carcinoma. J Cell Biochem. 2019 Oct;120(10):16692-16702. doi: 10.1002/jcb.28927.
18.Chen J, Li X, Zhong H, Meng Y*, Du H*. Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers. Sci Rep. 2019 Jun 27;9(1):9345. doi: 10.1038/s41598-019-45835-3.
19.Zhang W, Meng Y, Fu S, Li X, Chen Z, Huang L, Du H*. Transcriptome Changes of Skeletal Muscle RNA-Seq Speculates the Mechanism of Postprandial Hyperglycemia in Diabetic Goto-Kakizaki Rats During the Early Stage of T2D. Genes (Basel). 2019 May 28;10(6):406. doi: 10.3390/genes10060406.
20.Fu S, Meng Y, Zhang W, Wang J, He Y, Huang L, Chen H, Kuang J, Du H*. Transcriptomic Responses of Skeletal Muscle to Acute Exercise in Diabetic Goto-Kakizaki Rats. Front Physiol. 2019 Jul 9;10:872. doi: 10.3389/fphys.2019.00872.
21.Meng Y, Cui Y, Zhang W, Fu S, Huang L, Dong H, Du H*. Integrative Analysis of Genome and Expression Profile Data Reveals the Genetic Mechanism of the Diabetic Pathogenesis in Goto Kakizaki (GK) Rats. Front Genet. 2019 Jan 10;9:724. doi: 10.3389/fgene.2018.00724.
22.Liang J, Cui Y, Meng Y, Li X, Wang X, Liu W, Huang L, Du H*. Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer. Funct Integr Genomics. 2019 Jan;19(1):191-204. doi: 10.1007/s10142-018-0636-6.
23.Yu X, Liang J, Xu J, Li X, Xing S, Li H, Liu W, Liu D, Xu J, Huang L, Du H*. Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data. J Breast Cancer. 2018 Dec;21(4):363-370. doi: 10.4048/jbc.2018.21.e56.
24.Fan, W., Peng, Y., Meng, Y, Zhang W, Zhu N, Wang J, Guo Ch, Li J, Du H*, Dang Z*. Transcriptomic Analysis Reveals Reduced Inorganic Sulfur Compound Oxidation Mechanism in Acidithiobacillus ferriphilus. Microbiology (2018) 87: 486. https://doi.org/10.1134/S0026261718040070
25.Meng Y, Guan Y, Zhang W, Wu YE, Jia H, Zhang Y, Zhang X, Du H*, Wang X. RNA-seq analysis of the hypothalamic transcriptome reveals the networks regulating physiopathological progress in the diabetic GK rat. Sci Rep. 2016, 6:34138. doi: 10.1038/srep34138.
26.Chen J, Meng Y, Zhou J, Zhuo M, Ling F, Zhang Y, Du H*, Wang X. Identifying candidate genes for Type 2 Diabetes Mellitus and obesity through gene expression profiling in multiple tissues or cells. J Diabetes Res. 2013, 2013:970435. doi:10.1155/2013/970435.
27.Jinghui Zhou, Yuhuan Meng, Shuai Tian, Junhui Chen, Mingyu Liu, Min Zhuo, Yu Zhang, Hongli Du*, and Xiaoning Wang. Comparative MicroRNA Expression Profiles of Cynomolgus Monkeys, Rat, and Human Reveal that miR-182 Is Involved in T2D Pathogenic Processes, J Diabetes Res, 2014, 760397
28.Wang Yu, Li W, Xia Y, Wang C, Tang YT, Guo W, Li J, Zhao X, Sun Y, Hu J, Zhen H, Zhang X, Chen C, Shi Y, Li L, Cao H, Du H*, Li J. Identifying Human Genome-Wide CNV, LOH and UPD by Targeted Sequencing of Selected Regions. PLoS One, 2015, 10(4):e0123081.
29.Li Y, Zheng H, Luo R, Wu H, Zhu H, Li R, Cao H, Wu B, Huang S, Shao H, Ma H,Zhang F, Feng S, Zhang W, Du H, Tian G, Li J, Zhang X, Li S, Bolund L,Kristiansen K, de Smith AJ, Blakemore AI, Coin LJ, Yang H, Wang J, Wang J. Structural variation in two human genomes mapped at single-nucleotide resolution by whole genome de novo assembly. Nature Biotechnology. 2011,29(8):723-730
30.Yan G, Zhang G, Fang X, Zhang Y, Li C, Ling F, Cooper DN, Li Q, Li Y, van Gool AJ, Du H, Chen J, Chen R, Zhang P, Huang Z, Thompson JR, Meng Y, Bai Y, Wang J, Zhuo M, Wang T, Huang Y, Wei L, Li J, Wang Z, Hu H, Yang P, Le L, Stenson PD, Li B, Liu X, Ball EV, An N, Huang Q, Zhang Y, Fan W, Zhang X, Li Y, Wang W, Katze MG, Su B, Nielsen R, Yang H, Wang J, Wang X, Wang J. Genome sequencing and comparison of two nonhuman primate animal models, the cynomolgus and Chinese rhesus macaques. Nature Biotechnology. 2011, 29(11):1019-23.
