Guojie Zhong  
(钟 国杰)

PhD Candidate, Department of Systems Biology, Columbia University.


Columbia University

Dept. of Systems Biology

1130 St. Nicholas Avenue

New York, NY 10032

I am currently a PhD student in Dr. Yufeng Shen’s lab at Department of Systems Biology, Columbia University.

My research is driven by the ultimate goal to bridge the gap between complex human diseases and effective treatments. To achieve this, I develop biologically-inspired machine learning algorithms that can be applied to high-throughput genomics data to uncover disease mechanisms. My past works expanded several areas including:

  1. Single cell spatial transcriptomics: CSOmap
  2. Statistical genetics: VBASS
  3. Missense variant effect predictions: PreMode

My future research interests include:

  1. Disease mechanism discovery utilizing high-throughput screening techniques and deep learning.
  2. Generative deep learning models of proteins, DNAs and RNAs.

Prior to Columbia, I got my B.S. in Integrated Science Program at Peking University with training mostly in biology, statistics and computer science. I joined Dr. Zemin Zhang’s Lab for my undergraduate thesis on developing computational methods to infer cellular spatial organization and cellular interaction from single cell genomics data.

I enjoy playing fingerstyle guitar and badminton in my free time, which both require a balance of power and control.

selected publications

  1. PreMode predicts mode of action of missense variants by deep graph representation learning of protein sequence and structural context
    Guojie Zhong, Yige Zhao, Demi Zhuang, Wendy K Chung, and Yufeng Shen
    bioRxiv 2024
  2. A probabilistic graphical model for estimating selection coefficient of missense variants from human population sequence data
    Yige Zhao, Guojie Zhong, Jake Hagen, Hongbing Pan, Wendy K. Chung, and 1 more author
    medRxiv 2023
  3. VBASS enables integration of single cell gene expression data in Bayesian association analysis of rare variants
    G. Zhong, Y. A. Choi, and Y. Shen
  4. MLSB 2022
    Representation of missense variants for predicting modes of action
    G. Zhong, and Y. Shen
    Machine Learning in Structural Biology, Workshop at the 36th Conference on Neural Information Processing Systems (NeurIPS), 2022
  5. Statistical models of the genetic etiology of congenital heart disease
    G. Zhong, and Y. Shen
    Curr Opin Genet Dev, 2022
  6. Identification and validation of candidate risk genes in endocytic vesicular trafficking associated with esophageal atresia and tracheoesophageal fistulas
    G. Zhong*, P. Ahimaz*, N. A. Edwards*, J. J. Hagen, C. Faure, and 13 more authors
    HGG Adv, 2022
  7. Reconstruction of cell spatial organization from single-cell RNA sequencing data based on ligand-receptor mediated self-assembly
    X. Ren*, G. Zhong*, Q. Zhang, L. Zhang, Y. Sun, and 1 more author
    Cell Res, 2020
  8. Landscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma
    Q. Zhang, Y. He, N. Luo, S. J. Patel, Y. Han, and 20 more authors
    Cell, 2019