Sai Zhang

Sai Zhang,

Assistant Professor

Department: Department of Epidemiology
Business Phone: (352) 273-5468
Business Email: sai.zhang@ufl.edu

About Sai Zhang

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

2023
Low expression of EXOSC2 protects against clinical COVID-19 and impedes SARS-CoV-2 replication
Life Science Alliance. 6(1) [DOI] 10.26508/lsa.202201449. [PMID] 36241425.
2022
A review of Mendelian randomization in amyotrophic lateral sclerosis
Brain. 145(3):832-842 [DOI] 10.1093/brain/awab420. [PMID] 34791088.
2022
Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
Briefings in Bioinformatics. 23(5) [DOI] 10.1093/bib/bbac331.
2022
Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis
Neuron. 110(6):992-1008.e11 [DOI] 10.1016/j.neuron.2021.12.019. [PMID] 35045337.
2022
Longitudinally tracking personal physiomes for precision management of childhood epilepsy
PLOS Digital Health. 1(12) [DOI] 10.1371/journal.pdig.0000161. [PMID] 36812648.
2022
Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity
Cell Systems. 13(8):598-614.e6 [DOI] 10.1016/j.cels.2022.05.007. [PMID] 35690068.
2022
Precision environmental health monitoring by longitudinal exposome and multi-omics profiling
Genome Research. 32(6):1199-1214 [DOI] 10.1101/gr.276521.121. [PMID] 35667843.
2022
Systems analysis of de novo mutations in congenital heart diseases identified a protein network in the hypoplastic left heart syndrome
Cell Systems. 13(11):895-910.e4 [DOI] 10.1016/j.cels.2022.09.001. [PMID] 36167075.
2022
Unbiased metabolome screen leads to personalized medicine strategy for amyotrophic lateral sclerosis
Brain Communications. 4(2) [DOI] 10.1093/braincomms/fcac069. [PMID] 35441136.
2021
Advances in the genetic classification of amyotrophic lateral sclerosis
Current Opinion in Neurology. 34(5):756-764 [DOI] 10.1097/wco.0000000000000986.
2021
Characterizing RNA Pseudouridylation by Convolutional Neural Networks
Genomics, Proteomics & Bioinformatics. 19(5):815-833 [DOI] 10.1016/j.gpb.2019.11.015. [PMID] 33631424.
2021
DeepRibSt: a multi-feature convolutional neural network for predicting ribosome stalling
Multimedia Tools and Applications. 80(11):17239-17255 [DOI] 10.1007/s11042-020-09598-8.
2021
Membrane lipid raft homeostasis is directly linked to neurodegeneration
Essays in Biochemistry. 65(7):999-1011 [DOI] 10.1042/ebc20210026.
2021
Physical exercise is a risk factor for amyotrophic lateral sclerosis: Convergent evidence from Mendelian randomisation, transcriptomics and risk genotypes
EBioMedicine. 68 [DOI] 10.1016/j.ebiom.2021.103397. [PMID] 34051439.
2021
Precision medicine in women with epilepsy: The challenge, systematic review, and future direction
Epilepsy & Behavior. 118 [DOI] 10.1016/j.yebeh.2021.107928. [PMID] 33774354.
2020
Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene
Cell Reports. 33(9) [DOI] 10.1016/j.celrep.2020.108456. [PMID] 33264630.
2019
DeepHINT: understanding HIV-1 integration via deep learning with attention
Bioinformatics. 35(10):1660-1667 [DOI] 10.1093/bioinformatics/bty842.
2019
Gene-Environment Interaction in the Era of Precision Medicine
Cell. 177(1):38-44 [DOI] 10.1016/j.cell.2019.03.004. [PMID] 30901546.
2018
Decoding the Genomics of Abdominal Aortic Aneurysm
Cell. 174(6):1361-1372.e10 [DOI] 10.1016/j.cell.2018.07.021.
2018
Reconstructing spatial organizations of chromosomes through manifold learning
Nucleic Acids Research. 46(8):e50-e50 [DOI] 10.1093/nar/gky065. [PMID] 29408992.
2017
A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data
Nucleic Acids Research. 45(14):e129-e129 [DOI] 10.1093/nar/gkx492. [PMID] 28575488.
2017
Analysis of Ribosome Stalling and Translation Elongation Dynamics by Deep Learning
Cell Systems. 5(3):212-220.e6 [DOI] 10.1016/j.cels.2017.08.004.
2017
Elastic restricted Boltzmann machines for cancer data analysis
Quantitative Biology. 5(2):159-172 [DOI] 10.1007/s40484-017-0092-7.
2017
TITER: predicting translation initiation sites by deep learning
Bioinformatics. 33(14):i234-i242 [DOI] 10.1093/bioinformatics/btx247. [PMID] 28881981.
2016
A deep learning framework for modeling structural features of RNA-binding protein targets
Nucleic Acids Research. 44(4):e32-e32 [DOI] 10.1093/nar/gkv1025. [PMID] 26467480.
2016
Constructing Structure Ensembles of Intrinsically Disordered Proteins from Chemical Shift Data
Journal of Computational Biology. 23(5):300-310 [DOI] 10.1089/cmb.2015.0184. [PMID] 27159632.

Grants

Dec 2023 ACTIVE
Combining genetics and single-cell multiomics to uncover cell-specific ALS mechanisms
Role: Principal Investigator
Funding: UNIVERSITY OF SHEFFIELD via Motor Neurone Disease Association

Education

Ph.D. in Computer Science and Technology
2017 · Tsinghua University
M.E. in Computer Technology
2013 · Tsinghua University
B.E. in Computer Science and Technology
2010 · Nanjing University of Science and Technology

Contact Details

Phones:
Business:
(352) 273-5468
Emails:
Business:
sai.zhang@ufl.edu
Addresses:
Business Street:
2004 MOWRY RD
GAINESVILLE FL 32611