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Lin
Xueqiu Lin, PhD
- Assistant Professor, Herbold Computational Biology Program, Public Health Sciences Division, Fred Hutch
- Member, Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch
Background
Computational biologist Dr. Xueqiu Lin’s lab focuses on developing cutting-edge computational and experimental approaches to uncover interactive rules within these regulatory networks and to understand the functional consequences of non-coding mutations. She focuses on the development of multiplexed CRISPR screening to study the functional interaction network of enhancers, or transcription factors. The use of this approach, combined with deep learning and statistical modeling, can reveal the genetic codes, discover novel genetic biomarkers and develop more accurate genomic risk prediction schemes for precision cancer medicine. She was also named as a STAT Wunderkind in 2023 for “shining a light on the general principles of gene expression.”
Education
Stanford University, CA, 2023, Postdoctoral training (Bioengineering and Bioinformatics)
Baylor College of Medicine, Houston, TX, 2017, Visiting student scholar (Bioinformatics)
Tongji University, Shanghai, China, 2016, PhD (Bioinformatics)
Sun Yat-Sen University, Guangzhou, China, 2011, BS
Research Interest
Using a combination of deep learning, multiplexed CRISPR screen and statistical modeling to:
- Deep learning, multiplexed CRISPR screening and statistical modeling
- Developing high-throughput multiplexed screens to study the functional interaction in non-coding genome
- Decoding the principles of genome regulation
- Modeling the epistasis consequences of multiple non-coding variants in cancer risk, autoimmune diseases and aging
- Developing broad targeting tools for human disease genomes and virus genomes