Sai Zhang
Assistant Professor
On This Page
About Sai Zhang
Teaching Profile
Courses Taught
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PHC7979 – Advanced Research
College of Public Health and Health Professions
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PHC6940 – Master of Public Health Capstone
College of Public Health and Health Professions
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PHC7980 – Research for Doctoral Dissertation
College of Public Health and Health Professions
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PHC7918 – Epidemiology Independent Study
College of Public Health and Health Professions
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PHC6937 – Special Topics in Public Health
College of Public Health and Health Professions
Research Profile
Our research lies at the interface of machine learning, genomics, and precision medicine. Our long-term goal is to build machine learning systems to assist scientific discovery, clinical decision making, and personal health management. The focus of our ongoing research is the development of machine learning algorithms (e.g., deep learning and probabilistic graphical models) which exploit massive genetic, multiomic, and clinical data to uncover the genomic basis of complex human diseases. Specifically, our work follows a variant-gene-pathway principle where we start from deep learning modeling of biological sequences (e.g., DNA and RNA) to predict functional effects of variants in different cellular processes (i.e., in silico mutagenesis; NAR 2016, Cell Systems 2017, Bioinformatics 2017). We then move on to a global modeling of genotype-phenotype mapping where we identify candidate risk genes (Neuron 2022, Cell Systems 2022) and predict phenotypes from personal genomes (Cell 2018). By leveraging cutting-edge techniques (e.g., deep learning and single-cell genomics), we are particularly interested in modeling the complexity (e.g., nonlinearity and cell-type-specificity) of the underlying biological system (Cell 2019).
Areas of Interest
- Computational biology
- Genetics
- Genomics
- Machine Learning
- Precision Medicine
Publications
Academic Articles
Grants
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Deep Learning for Single-Cell Genetics
Active
- Role:
- Principal Investigator
- Funding:
- NATL INST OF HLTH NIGMS
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Deciphering the genetic basis of cellular heterogeneity in ALS via deep learning
- Role:
- Principal Investigator
- Funding:
- JOHNS HOPKINS UNIVERSITY
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Combining genetics and single-cell multiomics to uncover cell-specific ALS mechanisms
Active
- Role:
- Project Manager
- Funding:
- UNIVERSITY OF SHEFFIELD via Motor Neurone Disease Association
Education
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Ph.D. in Computer Science and Technology
Tsinghua University
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M.E. in Computer Technology
Tsinghua University
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B.E. in Computer Science and Technology
Nanjing University of Science and Technology
Contact Details
- Business:
- (352) 273-5468
- Business:
- sai.zhang@ufl.edu
- Business Street:
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2004 MOWRY RD
GAINESVILLE FL 32611