Sai Zhang, PhD
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Assistant Professor of Biomedical Informatics and Data ScienceDownloadHi-Res Photo
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Assistant Professor of Biomedical Informatics and Data Science
Biography
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Sai Zhang received his PhD in Computer Science from Tsinghua University, where he trained in machine learning and computational biology. He completed postdoctoral training in the Department of Genetics at Stanford University School of Medicine under the supervision of Dr. Michael Snyder, gaining extensive experience in disease genetics and genomics, and was subsequently promoted to an instructor.
Before moving to Yale, Zhang was an assistant professor at the University of Florida. The Zhang Laboratory focuses on developing advanced AI and machine learning models that integrate large-scale human genetics, single-cell multiomics, and clinical data, aiming to uncover the high-resolution biology of complex diseases, guide the development of novel therapeutics, and advance precision medicine. His research is currently supported by NIGMS R35 (MIRA), MND Association, Packard Center for ALS Research, and Target ALS.
Last Updated on June 02, 2026.
Appointments
Biomedical Informatics & Data Science
Assistant ProfessorPrimary
Other Departments & Organizations
Education & Training
- Postdoctoral Scholar
- Stanford University School of Medicine (2021)
- PhD
- Tsinghua University, Computer Science (2017)
- ME
- Tsinghua University, Computer Technology (2013)
- BE
- Nanjing University of Science & Technology, Computer Science (2010)
Research
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Overview
Medical Research Interests
Artificial Intelligence; Computational Biology; Genetics; Genomics; Machine Learning; Precision Medicine
ORCID
0000-0001-5996-6086
Research at a Glance
Yale Co-Authors
Frequent collaborators of Sai Zhang's published research.
Publications Timeline
A big-picture view of Sai Zhang's research output by year.
Research Interests
Research topics Sai Zhang is interested in exploring.
Chao Cheng
35Publications
1,510Citations
Computational Biology
Machine Learning
Genomics
Precision Medicine
Publications
Featured Publications
Single-cell polygenic risk scores dissect cellular and molecular heterogeneity of complex human diseases
Zhang S, Shu H, Zhou J, Rubin-Sigler J, Yang X, Liu Y, Cooper-Knock J, Monte E, Zhu C, Tu S, Li H, Tong M, Ecker J, Ichida J, Shen Y, Zeng J, Tsao P, Snyder M. Single-cell polygenic risk scores dissect cellular and molecular heterogeneity of complex human diseases. Nature Biotechnology 2025, 44: 845-861. PMID: 40715455, PMCID: PMC13180658, DOI: 10.1038/s41587-025-02725-6.Peer-Reviewed Original ResearchThis study introduces scPRS, a graph neural network framework that improves genetic risk prediction and links genetic variants to cell-specific disease mechanisms for conditions like Alzheimer's and diabetes.Modeling gene interactions in polygenic prediction via geometric deep learning
Li H, Zeng J, Snyder M, Zhang S. Modeling gene interactions in polygenic prediction via geometric deep learning. Genome Research 2024, 35: gr.279694.124. PMID: 39562137, PMCID: PMC11789630, DOI: 10.1101/gr.279694.124.Peer-Reviewed Original ResearchCitationsAltmetric
2026
Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population.
Ieki H, Zhang S, Koyama S, Kjellberg M, Yoshida H, Kurosawa R, Matsunaga H, Miyazawa K, Enzan N, Kim C, Seo J, Higasa K, Ozaki K, Onouchi Y, Matsuda K, Kamatani Y, Terao C, Matsuda F, Snyder M, Komuro I, Ito K. Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population. Circulation Genomic And Precision Medicine 2026, e005341. PMID: 42237915, PMCID: PMC13310176, DOI: 10.1161/circgen.125.005341.Peer-Reviewed Original ResearchAltmetric
2025
A single-cell, long-read, isoform-resolved case-control study of FTD reveals cell-type-specific and broad splicing dysregulation in human brain
Belchikov N, Hu W, Fan L, Joglekar A, He Y, Foord C, Jarroux J, Hsu J, Pollard S, Amin S, Prjibelski A, Gong S, Zhang S, Giannelli R, Seelaar H, Tomescu A, Ross M, Li A, Grinberg L, Spina S, Miller B, Cooper-Knock J, Snyder M, Seeley W, Rao-Ruiz P, Spijker S, Smit A, Clelland C, Gan L, Tilgner H. A single-cell, long-read, isoform-resolved case-control study of FTD reveals cell-type-specific and broad splicing dysregulation in human brain. Cell Reports 2025, 44: 116198. PMID: 40913764, PMCID: PMC12558363, DOI: 10.1016/j.celrep.2025.116198.Peer-Reviewed Original ResearchCitationsAltmetricEvaluation of a biomarker for amyotrophic lateral sclerosis derived from a hypomethylated DNA signature of human motor neurons
Harvey C, Nowak A, Zhang S, Moll T, Weimer A, Barcons A, Souza C, Ferraiuolo L, Kenna K, Zaitlen N, Caggiano C, Shaw P, Snyder M, Mill J, Hannon E, Cooper-Knock J. Evaluation of a biomarker for amyotrophic lateral sclerosis derived from a hypomethylated DNA signature of human motor neurons. BMC Medical Genomics 2025, 18: 10. PMID: 39810183, PMCID: PMC11734586, DOI: 10.1186/s12920-025-02084-w.Peer-Reviewed Original ResearchCitationsAltmetric
2024
PRS-Net: Interpretable Polygenic Risk Scores via Geometric Learning
Li H, Zeng J, Snyder M, Zhang S. PRS-Net: Interpretable Polygenic Risk Scores via Geometric Learning. Lecture Notes In Computer Science 2024, 14758: 377-380. DOI: 10.1007/978-1-0716-3989-4_35.ChaptersCitationsAltmetricRare and common genetic determinants of mitochondrial function determine severity but not risk of amyotrophic lateral sclerosis
Harvey C, Weinreich M, Lee J, Shaw A, Ferraiuolo L, Mortiboys H, Zhang S, Hop P, Zwamborn R, van Eijk K, Julian T, Moll T, Iacoangeli A, Al Khleifat A, Quinn J, Pfaff A, Kõks S, Poulton J, Battle S, Arking D, Snyder M, Consortium P, Veldink J, Kenna K, Shaw P, Cooper-Knock J. Rare and common genetic determinants of mitochondrial function determine severity but not risk of amyotrophic lateral sclerosis. Heliyon 2024, 10: e24975. PMID: 38317984, PMCID: PMC10839612, DOI: 10.1016/j.heliyon.2024.e24975.Peer-Reviewed Original ResearchCitationsAltmetric
2022
Longitudinally tracking personal physiomes for precision management of childhood epilepsy
Jiang P, Gao F, Liu S, Zhang S, Zhang X, Xia Z, Zhang W, Jiang T, Zhu J, Zhang Z, Shu Q, Snyder M, Li J. Longitudinally tracking personal physiomes for precision management of childhood epilepsy. PLOS Digital Health 2022, 1: e0000161. PMID: 36812648, PMCID: PMC9931296, DOI: 10.1371/journal.pdig.0000161.Peer-Reviewed Original ResearchCitationsAltmetricLow expression of EXOSC2 protects against clinical COVID-19 and impedes SARS-CoV-2 replication
Moll T, Odon V, Harvey C, Collins M, Peden A, Franklin J, Graves E, Marshall J, dos Santos Souza C, Zhang S, Castelli L, Hautbergue G, Azzouz M, Gordon D, Krogan N, Ferraiuolo L, Snyder M, Shaw P, Rehwinkel J, Cooper-Knock J. Low expression of EXOSC2 protects against clinical COVID-19 and impedes SARS-CoV-2 replication. Life Science Alliance 2022, 6: e202201449. PMID: 36241425, PMCID: PMC9585911, DOI: 10.26508/lsa.202201449.Peer-Reviewed Original ResearchCitationsAltmetricSystems analysis of de novo mutations in congenital heart diseases identified a protein network in the hypoplastic left heart syndrome
Wang Y, Zhang X, Lam C, Guo H, Wang C, Zhang S, Wu J, Snyder M, Li J. Systems analysis of de novo mutations in congenital heart diseases identified a protein network in the hypoplastic left heart syndrome. Cell Systems 2022, 13: 895-910.e4. PMID: 36167075, PMCID: PMC9671831, DOI: 10.1016/j.cels.2022.09.001.Peer-Reviewed Original ResearchCitationsAltmetric
Academic Achievements & Community Involvement
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Activities
activity PLOS Computational Biology
2025 - PresentJournal ServiceGuest Editoractivity Research in Computational Molecular Biology (RECOMB)
2024 - 2026Peer Review Groups and Grant Study SectionsProgram Committeeactivity Intelligent Systems for Molecular Biology (ISMB)
2026 - 2026Meeting Planning and ParticipationArea Chairactivity Tsinghua University
2023 - 2025Public ServiceExternal Examiner of PhD Thesisactivity Motor Neurone Disease Association
2023 - 2025Peer Review Groups and Grant Study SectionsGrant Reviewer
Honors
honor Maximizing Investigators' Research Award (MIRA) for Early Stage Investigators (R35)
04/18/2025National AwardNational Institute of General Medical Sciences (NIGMS)
Teaching & Mentoring
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Mentoring
Yiran Wang
Postgrad associate2026 - PresentTian Lan
Postdoctoral Associate2025 - PresentYurui Chen
Postdoctoral Associate2025 - Present
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101 College Street
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Fl 10, Rm 1021N
New Haven, CT 06510