Our lab

Chen Jinmiao Lab

Single-Cell Multi/Spatial-Omics and Precision Immunology

Bioinformatics Institute (BII), A*STAR · Duke-NUS Medical School

About

The Chen Jinmiao Lab is a multidisciplinary computational biology research laboratory spanning the Bioinformatics Institute (BII) at the Agency for Science, Technology and Research (A*STAR) and Duke-NUS Medical School in Singapore.

To advance biomedical discovery and precision medicine through innovative artificial intelligence, computational biology, and integrative single-cell and spatial omics research.

Principal Investigator

Associate Professor Jinmiao Chen

  • Senior Principal Investigator, A*STAR Bioinformatics Institute
  • Associate Professor, Duke-NUS Medical School
  • Associate Professor, NUS Yong Loo Lin School of Medicine

Associate Professor Jinmiao Chen is a computational biologist specializing in artificial intelligence, single-cell and spatial omics, and precision immunology.

A*STAR laboratory pageDuke-NUS directoryORCID

Team

A*STAR Bioinformatics Institute

  • Xu HangResearch Scientist
  • Raman SethiResearch Officer
  • Rom UddamvathanakResearch Officer
  • Laura SamPhD Student

Duke-NUS Medical School

  • Samueh ChuahResearch Scientist
  • Xiao MengResearch Scientist
  • Xu HuaResearch Scientist
  • Yan JunPhD Student
  • Yu LingPhD Student
  • Ren LiangruiResearch Scientist
  • KaijiePhD Student
  • Chen YiruPhD Student

Alumni

  • Yahui LongResearch Scientist, A*STAR BII
  • Li MengweiResearch Scientist, A*STAR BII
  • Zhong ChengweiResearch Officer, A*STAR BII

Research

  • Artificial Intelligence for Single-Cell Omics

    Computational and deep-learning approaches to study cellular diversity and biological processes using single-cell omics data.

  • Spatial Transcriptomics and Spatial Multi-Omics

    Methods to understand the spatial organization of cells and tissues by integrating gene expression with spatial and complementary molecular information.

  • Large-Scale Single-Cell Data Integration

    Computational resources and analytical tools for integrating publicly available single-cell datasets.

  • AI for Drug Discovery and Cellular Perturbations

    Computational approaches for modeling biological responses to drug treatment and genetic perturbations.

  • Precision Immunology and Virtual Immunity

    Computational biology and AI to characterize immune-cell states and investigate immune-system complexity.

Publications

Browse all 124 publications