Computational & Statistical Systems Biology Laboratory

@ Cardiovascular Research Institute, National University of Singapore

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We develop computational and statistical solutions for the analysis of high-dimensional molecular data in various contexts of biomedical research. These tools are motivated by a wide range of research topics, including

  • Integration of multi-omics data with biologically sensible interpretation of molecular features and robust outcome prediction
  • Development of in-house workflows for large-scale untargeted and targeted mass spectrometry (MS) data extraction in proteomics and metabolomics
  • Effect size-driven analysis approaches for protein modifications, interactions, and other applications of proteomics
  • Using single-cell data as a prior information to make cell population-level inference from bulk -omics data
  • Interactive data visualization and exploration of high-dimensional data
  • Clinical application of sequencing and mass spectrometry-based omics platforms

To see examples of our work, check out the CSSB LAB GitHub page!

Latest News

4 July 2020: iOmicsPASSv2, an extension of the first method paper at npj Systems Biology and Applications, is coming soon! The new software is equipped with new functionalities to infer bona fide partial correlation networks from omics datasets, and is applicable to cell/tissue analysis as well as circulating marker analysis using multi-omics data.

4 July 2020: Highly flexible multi-omics visualization tool multiSLIDE will be released soon. In combination with single omics data visualization SLIDE, multiSLIDE enables visualization of multiple omics data sets from genomics to metabolomics, revealing intricate relationship in molecular variations across different omics data sets.

4 July 2020: Michael Washburn at Stowers Institute and I are editing a special issue on Computational Approaches in Multi-omics Analysis in Molecular Omics. We are still accepting articles -- consider contributing to the special issue.

3 July 2020: Our new tool, MRMkit, for fully automated peak integration and data normalization for large-scale targeted mass spectrometry is available on GitHub. Imagine MRM analysis of thousands of samples with hundreds of transitions, fully cleaned up within several hours or less on your desktop!

14 May 2020: A new paper on MetaboKit for untargeted metabolomics analysis using data dependent and data independent acquisition modes of mass spectrometry has been accepted at Molecular Omics. Check out the GitHub repository!

20 January 2020: Our latest work on exome variant aggregation approach on protein sequence units (GPD) is in Human Mutation.


Contact Information

Principal Investigator: Hyungwon Choi

Computational & Statistical Systems Biology Lab

Cardiovascular Research Institute

Department of Medicine, Yong Loo Lin School of Medicine

National University of Singapore

Email: hwchoi [ at ] nus.edu.sg

Twitter: http://twitter.com/cssblab_nus


HC is an editorial board member at Molecular Omics -- feel free to discuss submission of your manuscript.