Li Qiyuan

Li Qiyuan

Title: Professor, Ph.D Supervisor

Degree: Ph.D

Department: National Research Institute of Health and Medical Big Data

Research field: Translational Medicine, Computational Biology, Genomics

Research Focus:

Mainly engaged in translational medicine research on tumor genome, using statistical models to find determinants related to clinical features such as tumor classification, prognosis, targeted therapy sensitivity and other clinical features from multi-omics data such as genetic polymorphism, somatic variation, epigenomics and gene expression, and explain their regulatory mechanisms; On this basis, a complex network model based on multi-omics association is established, and artificial intelligence methods are applied to discover new tumor driver genes. It was selected into the National High-level Talent Youth Project, Xiamen "Double Hundred Plan", Xiamen High-level Talent Special Project, etc.

 

 

Education Background:

 1996~2000: East China University of Science and Technology, B.S.;

2000~2003: Master of Cell Biology, Xiamen University;

2004~2006: Master of Bioinformatics, Technical University of Denmark;

2006~2010: Ph.D. in Systems Biology, Technical University of Denmark.

 

Work experience:

2010.03~2012.03: Postdoctoral Fellow, Harvard Cancer Center;

2012.05~2017.11: Associate Professor, School of Medicine, Xiamen University;

2017.11~Present : Professor, School of Medicine, Xiamen University; Deputy Dean of the National Institute of Health and Medicine, Xiamen University

2015~2022:  Deputy Director of Pediatric Internal Medicine Research of the First Affiliated Hospital of Xiamen University, carrying out pediatric hereditary defect screening and scientific research support;

 

Selected Publications:

1. Li Y, Zou L, Li Q, et al. Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer[J]. Nature Medicine, 2010, 16(2):214.

2. Li Q, Seo J H, Stranger B, et al. Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci[J]. Cell, 2013, 152(3):633-41.

3. Lawrenson K, Li Q, Kar S, et al. Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer[J]. Nature Communications, 2015, 6:8234

4. Jintao Guo , Jiankun Huang , Ying Zhou , Yulin Zhou , Liying Yu, Huili Li , Lingyun Hou , Liuwei Zhu , Dandan Ge , Yuanyuan Zeng , Bayasi Guleng* and Qiyuan Li*. Germline and somatic variations influencethe somatic mutational signatures of esophageal squamous cell carcinomas in a Chinese population . BMC Genomics,(2018) 19:538

5. Ke Liu , Jintao Guo , Kuai Liu , Peiyang Fan , Yuanyuan Zeng, Chaoqun Xu, Jiaxin Zhong , Qiyuan Li*, Ying Zhou *. Integrative analysis reveals distinct subtypes with therapeutic implications in KRAS-mutant lung adenocarcinoma . EBioMedicine 36 (2018) 196–208

6. Wu J, Zhong T, Zhu Y, Ge D, Lin X, Li Q*. Effects of particulate matter (PM) on childhood asthma exacerbation and control in Xiamen, China. BMC Pediatrics,  (2019) 19:194

7. Li W, Xu C, Guo J, Liu K, Hu Y, Zou Y, Wei Z, Wang Z, Zhou Y, Li Q. "Cis-and Trans-acting Expression Quantitative Trait Loci of Long Non-coding RNA in 2,549 cancers with potential clinical and therapeutic implications." Frontiers in Oncology 10 (2020): 2279.

8. Wu, J, et al. "IRF4 and STAT3 activities are associated with the imbalanced differentiation of T-cells in responses to inhalable particulate matters." Respiratory Research 21.1 (2020): 1-13