LIN, Zhixiang 林志翔

Position Assistant Professor
Email zhixianglin [at]
Phone Number 3943 7921
Fax Number 2603 5188
Address LSB 118A

Academic Background

B.S. in Biological Sciences, Tsinghua University
Ph.D. in Biomathematics, Bioinformatics and Computational Biology, Yale University

Research Interest

Selected Publications

(updated on July 12, 2024; see homepage for full up-to-date list; homepage requires access to Google)

In the author list, boldface indicates group members; * represents equal contribution; and  represents the corresponding author.

  1. Zhao K, Huang S, Lin C, Sham PC, So HC†, Lin Z†: INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis. PLoS Genetics 2024, 20(3): e1011189. [paper link]
  2. Li J, Wang J, and Lin Z†: SGCAST: symmetric graph convolutional auto-encoder for scalable and accurate study of spatial transcriptomicsBriefings in Bioinformatics 2024, 25(1), bbad490. [paper link]
  3. Li C, Chan TF, Yang C† and Lin Z†: stVAE deconvolves cell-type composition in large-scale cellular resolution spatial transcriptomics. Bioinformatics 2023, 39(10), btad642. [paper link]
  4. Wan X*, Xiao J*, Tam S, Cai M, Sugimura R, Wang Y, Wan X, Lin Z†, Angela Ruohao Wu AR† and Yang C†: SpatialScope: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models. Nature Communications, 2023, 14: 7848. [paper link]
  5. Zhang Z, Chen S, Lin Z†: RefTM: reference-guided topic modeling of single-cell chromatin accessibility data. Briefings in Bioinformatics 2022, bbac540. [paper link]
  6. Zeng P, Ma Y, Lin ZscAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data. Bioinformatics 2022, btac739. [paper link]
  7. Ming J*, Lin Z*, Wan X, Yang C†, Wu AR†: FIRM: Fast Integration of single-cell RNA-sequencing data across Multiple platforms. Briefings in Bioinformatics 2022, 23(5): bbac167. [paper link]
  8. Hu X*, Zhao J*, Lin Z, Wang Y, Peng H, Zhao H†, Wan X†, Yang C†: MR-APSS: a unified approach to Mendelian Randomization accounting for pleiotropy and sample structure using genome-wide summary statistic. Proceedings of the National Academy of Sciences of the United States of America 2022, 119(28): e2106858119. [paper link]
  9. Ma Y, Sun Z, Zeng P, Zhang W, Lin Z: JSNMF enables effective and accurate integrative analysis of single-cell multiomics data. Briefings in Bioinformatics 2022, bbac105. [paper link]
  10. Wangwu J, Sun ZLin Z: scAMACE: Model-based approach to the joint analysis of single-cell data on chromatin accessibility, gene expression and methylation. Bioinformatics 2021, 37(21):3874–3880. [paper link]
  11. Chen S*, Yan G*Zhang W, Li J, Jiang RLin Z: RA3 is a reference-guided approach for epigenetic characterization of single cells. Nature Communications 2021, 12:2177. [paper link]
  12. Zeng PLin Z: coupleCoC+: an information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data. PLOS Computational Biology 2021, 17(6): e1009064. [paper link]
  13. Zeng PWangwu J, Lin Z: Coupled Co-clustering-based Unsupervised Transfer Learning for the Integrative Analysis of Single-Cell Genomic Data.  Briefings in Bioinformatics 2020, bbaa347. [paper link]
  14. Zhang S, Yang L, Yang JLin Z, Ng KM: Dimensionality reduction for single cell RNA sequencing data using constrained robust non-negative matrix factorization. NAR Genomics and Bioinformatics 2020, 2(3): lqaa064. [paper link]
  15. Lin Z, Zamanighomi M, Daley T, Ma S and Wong WH: Model-based approach to the joint analysis of single-cell data on chromatin accessibility and gene expression. Statistical Science 2020, 35(1):2-13. [paper link]
  16. Zhang WWangwu J and Lin Z: Weighted K-means Clustering with Observation Weight for Single-cell Epigenomic Data. Statistical Modeling in Biomedical Research, book chapter p37-64. [paper link]
  17. Mingfeng Li, …, BrainSpan Consortium*, …, Nenad Sestan: Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science. 2018, 362:6420. BrainSpan Consortium*: Zhixiang Lin is a member of the BrainSpan consortium. In the collaboration with Nenad Sestan, the method AC-PCA is implemented in this paper for novel biological findings.
  18. Daley T†, Lin Z, Bhate S, Lin X, Liu Y, Wong, WH, and Qi L: CRISPhieRmix: a hierarchical mixture model for CRISPR pooled screens. Genome Biology. 2018, 19:159.
  19. Zamanighomi M*, Lin Z*, Daley T*, Chen Xi , Zhana Duren, Schep A, Greenleaf WJ, and Wong WH: Unsupervised clustering and epigenetic classification of single cells. Nature Communications. 2018, 9:2410. [paper link] [software link]
  20. Zamanighomi M, Lin Z, Wang Y, Jiang R, and Wong WH: Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility, and gene expression data. Nucleic Acids Research. 2017, 45(10): 5666-5677. [paper link]
  21. Lin Z, Wang T, Yang C, and Zhao H: On joint estimation of Gaussian graphical models for spatial and temporal data. Biometrics. 2017, 73: 769-779. [paper link] [software link]
  22. Lin Z, Yang C, Zhu Y, Duchi JC, Fu Y, Wang Y, Jiang B, Zamanighomi M, Xu X, Li M, Sestan N, Zhao H, and Wong WH: Simultaneous dimension reduction and adjustment for confounding variation. Proceedings of the National Academy of Sciences of the United States of America. 2016, 113 (51): 14662-14667. [paper link] [software link]
  23. Lin Z, Sanders SJ, Li M, Sestan N, State MW and Zhao HA Markov Random Field-based approach to characterizing human brain developments using spatial-temporal transcriptome dataAnnals of Applied Statistics 2015, 9 (1): 429-451. [paper link]
  24. Willsey AJ, Sanders SJ, Li M, Tebbenkamp AT, Muhle RA, Reilly SK, Lin Z, Fertuzinhos S, Miller JA, Murtha MT, Bichsel C, Niu W, Cotney J, Gulhan A, Gockley J, Gupta A, Han W, He X, Homan E, Klei L, Lei J, Liu W, Liu L, Lu C, Xu X, Zhu Y, Mane SM, Lein ES, Wei L, Noonan JP, Roeder K, Devlin B, Sestan N and State MWCo-expression networks implicate human mid-fetal deep cortical projection neurons in the pathogenesis of autismCell 2013, 155 (5): 997-1007.

Graduate Students

  • Zheng Zhang, PhD student, 2020-present
  • Jinzhao Li, PhD student, 2021-present
  • Xiaocheng Zhou, PhD student, 2022-present
  • Muyang Ge, PhD student, 2022-present
  • Jishuai Miao, PhD student, 2023-present
  • Ji Qi, PhD student, 2023-present

Past graduate students:

  • Wenyu Zhang, PhD student, 2019-2023
  • Jinzhao Li, MPhil student, 2019-2021
  • Jiaxuan Wangwu, PhD student, 2018-2022
  • Weiwei Xu, MPhil student, 2020-2022

Competitive External Research Grants

RGC-ECS 24301419, awarded by the Research Grants Council
Title: A unified framework for jointly modeling and clustering multiple data types in single-cell genomics
2019-2022, Principal Investigator
RGC-GRF 14301120, awarded by the Research Grants Council
Title: Statistical methods for dimension reduction in single-cell genomics leveraging bulk genomic data
2020-2023, Principal Investigator
RGC-GRF 14300923, awarded by the Research Grants Council
Title: A unified framework for jointly modeling and integrative analysis of single-cell multi-omics data
2023-2026, Principal Investigator


  • STAT4001 Data Mining and Statistical Learning
  • STAT4002 Applied Multivariate Analysis
  • STAT6205 Probabilistic Machine Learning


Honors and Awards

  • Predoctoral award in basic science, Association of Chinese Geneticists in America,  2012
  • (Awarded to my PhD student Jiaxuan Wangwu) Champion in 2021-2022 Science Faculty Postgraduate Research Day’s Best Presentation Award, CUHK
  • (Awarded to my PhD student Wenyu Zhang’s team) Champion in Huawei ICT Competition 2022-23 HKSAR

Professional Service

  • Invited Editor, Quantitative Biology (2021-05 to present) 
  • Membership: American Statistical Association, International Chinese Statistical Association

Reviewer for Journal of the American Statistical Association, Annals of Applied StatisticsBayesian Analysis, Biometrics, Statistica Sinica, Nature Biotechnology, PNAS, Genome Biology, Nucleic Acids Research, PLOS Computational Biology, Cell Systems, Briefings in Bioinformatics, and Bioinformatics



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