Biography

Dr. Siyang Liu is a tenured Associate Professor of Medical Bioinformatics at Zhongshan School of Medicine, Sun Yat-sen University. She received her BSc in Biology from Sun Yat-sen University in 2011, followed by an MSc and a PhD in Bioinformatics from the University of Copenhagen in 2015 and 2017, respectively. Before joining Sun Yat-sen University in 2021, she held positions as a Senior Bioinformatics Engineer and Senior Research Scientist at BGI.

Her research focuses on developing and applying large-scale data analytics, statistical genetics, and bioinformatics methods to elucidate disease mechanisms and advance therapeutic discovery, with a particular interest in major diseases affecting women and children. She has led research projects supported by the National Natural Science Foundation of China (NSFC) and Innovation Fund Denmark (Innovationsfonden). As a (co-)first or corresponding author, she has published her work in prestigious journals such as Cell, Nature, Nature Genetics, Blood, the Journal of Hepatology, and Nature Communications.

Current Position

Associate Professor, Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University

Additional Academic Appointments

• Member of State Key Laboratory of Reproductive Medicine and Offspring Health
• Member of Key Laboratory of Environment and Children’s Health, Ministry of Education and Shanghai Municipality
• Standing Committee Member, Environmental and Maternal–Child Health Committee, Chinese Environmental Mutagen Society
• Standing Committee Member, Multi-Omics Branch, Chinese Stroke Association
• Committee Member, Technical Committee on Digital Healthcare Systems Engineering, Systems Engineering Society of China

Professional Experience

• Jul 2026–Present | Associate Professor, Zhongshan School of Medicine, Sun Yat-sen University
• Jan 2021–Jul 2026 | Associate Professor, School of Public Health (Shenzhen), Sun Yat-sen University
• Jan 2020–Dec 2020 | Senior Research Scientist, BGI-Shenzhen Life-Science Institute
• Jan 2018–Dec 2019 | Senior Bioinformatics Engineer, BGI-Shenzhen Life-Science Institute

Education/Training

• 2015/05-2017/12 PhD in Bioinformatics, University of Copenhagen, Supervisor： Profs. Anders Krogh & Anders Albrechtsen
• 2012/09-2015/04 MSc in Bioinformatics, University of Copenhagen, Supervisor： Prof. Anders Krogh
• 2007/09-2011/07 BSc in Biology, Department of Life Science, Sun Yat-sen University

Teaching

• Programming for Medical Informatics
• Python and Data Science
• R Programming and Statistical Analysis
• Introduction to Artificial Intelligence
• Medical Statistics
• Bioinformatics

Grants

As Principal Investigator

• National Natural Science Foundation of China (NSFC), Young Scientists Fund (Category B) (formerly the Excellent Young Scientists Fund). Development and Application of Methods for Elucidating the Causes of Maternal and Infant Diseases Using Large-Scale Healthcare Data. Jan 2026–Dec 2028. Ongoing.
• NSFC, General Program. Development and Application of Life-Course Mendelian Randomization Methods to Investigate the Origins of Health and Disease. Jan 2025–Dec 2028. Ongoing.
• NSFC, Young Scientists Fund. Genome-Wide Association Studies Using Low-Coverage Sequencing Data. Jan 2020–Dec 2022. Completed.
• Guangdong Provincial Major Talent Program, Young Talent Scheme. Development and Application of Methods for Large-Scale Healthcare Data Analysis. Sep 2025–Sep 2028. Ongoing.
• Shenzhen Stable Support Program, General Project. Investigating the Causal Effects of Intrauterine Environmental Exposures on Child Growth and Development Using Intergenerational Mendelian Randomization. Sep 2022–Aug 2025. Completed.
• Sun Yat-sen University “3510” Medical Innovation Leadership Program, Key Project under the Clinical Basic Research Scheme. Jan 2026–Dec 2030. Ongoing.
• Sun Yat-sen University “Hundred Talents Program,” Start-up Grant. Jan 2021–Dec 2023. Completed.
• Innovation Fund Denmark. Apr 2015–Apr 2018. Completed.

As Participant

• National Key Research and Development Program of China. Core Research Team Member. Dec 2022–Dec 2025. Completed.
• National Key Research and Development Program of China. Core Research Team Member. Dec 2021–Nov 2024. Completed.
• Guangdong Provincial Basic and Applied Basic Research Regional Joint Fund, Key Project. Subproject Lead. Jan 2022–Sep 2025. Completed.

Representative Publications (# First authors; *Corresponding authors; Reverse chronological order)

1. Liu S#, Zheng H#, Gu Y#, Yang Z#, Zhen J#, Wei Y, Liu Y, Chen Y, Wan Z, Guo X, Hu L, Chen X, Li X, Qiu X, Huang S, Chen GB, Hu Z, Namba S, Kanai M, Matsuda K, Okada Y, Zhang Q*, Wei F*. Genome-wide association analyses of gestational phenotypes identify context-specific genetic effects. Nature Genetics. 2026 (Website: https://monn.pheweb.com/)
2. Li Y#, Lin YF#, Cai B, Chen F, Zhang Q, Liu S*, Zhen J*. Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies. BMC Medicine. 2026
3. Cheng S#, Wei Y#, Zheng H, Zhang Q, Yang X, Lu Z, Huang Z, Wan Z, Shi Y, Zhang J, Choi JC, Kang CH, Kim HJ, Kim JG, Bae HJ, Lee J, Lee JY, Jung H, Guo C, Liao X, Wu J, Meng X, Li Z, Debette S, Li H, Wang Y, Cheng S*, Liu S*. Artificial intelligence-powered delta-NIHSS-based model for predicting recurrence, disability and mortality after acute ischaemic strokes (DISCO): a modelling study. eClinicalMedicine. 2025 (Website: https://www.discosysu.cn/)
4. Gu Y#, Zheng H#, Wang P#, Liu Y, Guo X, Wei Y, Yang Z, Cheng S, Chen Y, Hu L, Chen X, Zhang Q, Chen G, Wei F*, Zhen J*, Liu S*. Genetic architecture and risk prediction of gestational diabetes mellitus in Chinese pregnancies. Nature Communications. 2025
5. Liu Y#, Wei Y#, Chen X#, Huang S#, Gu Y, Yang Z, Guo X, Zheng H, Feng H, Huang M, Chen S, Xiao T, Hu L, Zhang Q, Zhang Y, Chen G, Qiu X*, Wei F*, Zhen J*, Liu S*. Genetic study of intrahepatic cholestasis of pregnancy in Chinese women unveils East Asian etiology linked to historic HBV epidemic. Journal of Hepatology. 2025 (Cover Story)
6. Yang Z#, Hu L#, Zhen J#, Gu Y, Liu Y, Huang S, Wei Y, Zheng H, Guo X, Chen G, Yang Y, Xiong L*, Wei F*, Liu S*. Genetic Basis of Altered Platelet Counts and Gestational Thrombocytopenia in Pregnancy. Blood. 2024
7. Wei Y#, Zhen J#, Hu L#, Gu Y, Liu Y, Guo X, Yang Z, Zheng H, Cheng S, Wei F*, Xiong L*, Liu S*. Genome-wide association studies of thyroid-related hormones, dysfunction, and autoimmunity among 85,421 Chinese pregnancies. Nature Communications. 2024
8. Huang S#, Liu S#, Huang M#, He J#, Wang C, Wang T, Feng X, Kuang Y, Lu J, Gu Y, Xia X, Lin S, BIGCS Group, Zhou W, Fu Q, Xia H*, Qiu X*. The Born in Guangzhou Cohort Study enables generational genetic discoveries. Nature. 2024
9. Liu S#, Liu Y, Gu Y, Lin X, Zhu H, Liu H, Xu Z, Cheng S, Lan X, Huang M, Li H, Nielsen R, Davies R, Albrechtsen A, Chen G, Qiu X, Jin X, Huang S*. Utilizing non-invasive prenatal test sequencing data for human genetic investigation. Cell Genomics. 2024 (Cover Story)
10. Liu S#, Yao J#, Lin L#, Lan X#, Wu L#, He X#, Kong N, Li Y, Deng Y, Xie J, Zhu H, Wu X, Li Z, Xiong L, Wang Y, Ren J, Qiu X, Zhao W, Gao Y, Chen Y, Su F, Zhou Y, Rao W, Zhang J, Hou G, Huang L, Li L, Liu X, Nie C, Luo L, Zhao M, Liu Z, Chen F, Lin S, Zhao L, Fu Q, Jiang D, Yin Y, Xu X, Wang J, Yang H, Wang R, Niu J, Wei F*, Jin X*, Liu S*. Genome-wide association study of maternal plasma metabolites during pregnancy. Cell Genomics. 2024
11. Zhen J#, Gu Y#, Wang P, Wang W, Bian S, Huang S, Liang H, Huang M, Yu Y, Chen Q, Jiang G, Qiu X, Xiong L*, Liu S*. Genome-wide association and Mendelian randomisation analysis among 30,699 Chinese pregnant women identifies novel genetic and molecular risk factors for gestational diabetes and glycaemic traits. Diabetologia. 2024
12. Bian S#, Guo X#, Yang X, Wei Y, Yang Z, Cheng S, Yan J, Chen Y, Chen G, Du X, Francis S, Shu Y*, Liu S*. Genetic determinants of IgG antibody response to COVID-19 vaccination. The American Journal of Human Genetics. 2024
13. Cheng S, Zheng H, Wei Y, Lin X, Gu Y, Guo X, Fan Z, Li H, Cheng S*, Liu S*. Gut Microbiome and Stroke: a Bidirectional Mendelian Randomisation Study in East Asian and European Populations. Stroke and Vascular Neurology. 2024
14. Cheng S#, Xu Z#, Bian S, Chen X, Shi Y, Li Y, Duan Y, Liu Y, Lin J, Jiang Y, Jing J, Li Z, Wang Y, Meng X, Liu Y, Fang M, Jin X, Xu X, Wang J, Wang C, Li H, Liu S*, Wang Y*. The STROMICS genome study: deep whole genome sequencing and analysis of 10K Chinese patients with ischemic stroke reveal complex. Cell Discovery. 2023
15. Liu S#, Huang S#, Chen F#, Zhao L#, Yuan Y#, Francis S, Fang L, Li Z, Lin L, Liu R, Zhang Y, Xu H, Li S, Zhou Y, Liu Q, Walters R, Lin K, Ju J, Korneliussen T, Yang M, Fu Q, Wang J, Zhou L, Krogh A, Zhang H, Wang W, Chen Z, Yin Y, Yang H, Mao M, Shendure J, Wang J*, Albrechtsen A*, Jin X*, Nielsen R*, Xu X*. Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, Patterns of Viral Infections, and Chinese Population History. Cell. 2018

Patents

1. Base Mutation Detection Method and Apparatus Based on Sequencing Data, and Storage Medium. 2023. PCT/CN2019/086972. Granted in China, Europe, the United States, Hong Kong, Saudi Arabia, Vietnam, and Malaysia.
2. Method and Apparatus for Variant Detection Based on Genome Assembly. 2015. ZL201510043793.2. Granted in China.
3. Method, System, Computer Equipment, and Storage Medium for Predicting Stroke Prognosis. 2024119535280. Granted in China.
4. Method, Apparatus, Storage Medium, and Product for Predicting Gestational Diabetes Risk. 2025101592122.

Invited Conference Presentations (Past Five Years, in Reverse Chronological Order)

1. Siyang Liu. “Intrahepatic cholestasis of pregnancy in East Asian populations may be linked to a historical HBV epidemic.” XXVIII International Bile Acid Meeting: Bile Acids in Health and Disease 2026. Vienna, Austria. July 3, 2026.
2. Siyang Liu. “Mapping and characterizing the dynamic genetic architecture of over 100 gestational phenotypes in the Chinese population.” Interdisciplinary Forum on Public Health Frontiers, Child and Adolescent Health Branch, Chinese Preventive Medicine Association. Nanjing, China. May 2026.
3. Siyang Liu. “Investigating the potential causal effects of the maternal intrauterine proteomic and metabolomic environment on autism in offspring using intergenerational Mendelian randomization.” Inaugural Symposium of the Environmental and Maternal–Child Health Committee, Chinese Environmental Mutagen Society. Nanjing, China. May 2026.
4. Siyang Liu. “Developing and applying methods to elucidate the causes of maternal and infant diseases.” Third National Conference on Genome Informatics. Hangzhou, China. March 2026.
5. Siyang Liu. “Elucidating the genetic and environmental determinants of maternal and infant diseases and traits using large-scale healthcare data.” 2025 National Symposium of the Functional Genomics and Systems Biology Branch. Changsha, China. April 2025.
6. Siyang Liu. “Using sequencing data from non-invasive prenatal testing for medical genetics research.” 2024 National Symposium of the Genetics Society of China. Changsha, China. November 2024.
7. Shiyao Cheng and Siyang Liu. “Developing and validating DISCO: An accurate and explainable machine learning model for predicting composite post-stroke outcomes.” 31st Workshop of the International Stroke Genetics Consortium. Los Angeles, United States. September 26, 2024.
8. Siyang Liu. “STROMICS: Methods and advances in multi-omics research on stroke.” 10th Annual Conference of the Chinese Stroke Association and Tiantan International Stroke Conference. Beijing, China. June 14, 2024.
9. Siyang Liu. “An atlas of quantitative trait loci for 100 gestational phenotypes.” 57th European Human Genetics Conference. Berlin, Germany. June 3, 2024.
10. Siyang Liu. “Investigating the causal effect of inflammation on stroke recurrence using Mendelian randomization.” 30th Workshop of the International Stroke Genetics Consortium. Munich, Germany. April 24, 2024.
11. Siyang Liu. “A multi-trait genome-wide association study of 34,394 Chinese women reveals the genetic architecture of plasma metabolites during pregnancy.” International Conference on Bioinformatics and Computational Biology. Hangzhou, China. April 22, 2023.

Awards and Honors

• 2026 — Supervisor of an Outstanding Undergraduate Thesis, Sun Yat-sen University
• 2025 — Supervisor of an Outstanding Doctoral Dissertation, Sun Yat-sen University
• 2024 — Course Lead for R Programming and Statistical Analysis, recognized as a Shenzhen Higher Education “Outstanding Shared Course”
• 2024 — Supervisor of an Outstanding Master’s Thesis, Sun Yat-sen University
• 2023–2024 — Faculty Advisor to National Award and Guangdong Provincial First-Prize Winners, National Undergraduate Statistical Modeling Competition
• 2022 — Supervisor of an Outstanding Undergraduate Thesis, Sun Yat-sen University
• 2018 — Shenzhen Overseas High-Level Talent Program, Peacock Plan (Category B)
• 2018 — Major Scientific Achievement Award, BGI-Shenzhen Life-Science Institute
• 2012–2014 — Danish Government Scholarship
• 2007–2010 — National Scholarship, China