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Ho-Joon Lee, PhD

Research Scientist in Genetics
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About

Titles

Research Scientist in Genetics

Appointments

Education & Training

Research Fellow
Harvard Medical School (2015)
Postdoctoral Fellow
Harvard University (2009)
PhD
Free University of Berlin, Computational Biology (2008)
Doctoral Researcher
Max Planck Institute for Molecular Genetics (2008)
MA
Cambridge University, Part III Mathematics (DAMTP) (1999)
MSc
Swansea University, Quantum Fields and Symmetry (1999)
BSc
Yonsei University, Physics (1997)

Research

Overview

Two primary projects are (1) AI/ML of ischemic stroke etiology classification using electronic health records and MRI images in collaboration with Dr. Richa Sharma (1 patent pending; https://www.nature.com/articles/s41746-024-01120-w) (2) AI/ML meta-modeling for ligand-protein binding affinity prediction with the Gerstein lab (1 patent pending; https://arxiv.org/abs/2310.03946) and drug discovery applications for targeted protein degradation in collaboration with the Spiegel lab.

Previous projects include (1) single-cell systems immunology of West Nile virus infection with the Montgomery and Kleinstein labs (https://www.cell.com/iscience/fulltext/S2589-0042(23)02464-1) (2) single-cell multi-omics data analysis of zebrafish brains and embryos with the Giraldez lab (https://elifesciences.org/arti...).

In response to the COVID-19 pandemic, I worked on virus-host protein-protein interactions (PPIs) and computational drug discovery together with Dr. Prashant Emani (the Gerstein lab) as a COVID HASTE working group of the Yale School of Engineering and Applied Science (see Figure 1 below for an overview). The project on virus-host PPIs was partially supported by a seed grant from the Northeast Big Data Innovation Hub and a preprint has been published (https://nebigdatahub.org/a-lan...). As an additional effort, with help from two of my former colleagues, Dr. Vinayagam Arunachalam (Takeda Pharmaceuticals) and Dr. Yang-Yu Liu (Harvard Medical School, Brigham and Women's Hospital), I carried out controllability analysis of a directed human protein-protein interaction network for SARS-CoV-2 based on our previous paper (https://www.pnas.org/doi/10.10...). A preprint is available here, https://www.biorxiv.org/conten....

My previous research mostly concerned biological questions in systems biology and network medicine by developing algorithms and models through a combination of statistical/machine learning, information theory, and network theory applied to high-throughput multi-dimensional data. It covered genomics, transcriptomics, proteomics, and metabolomics from yeast to mouse to human for integrative analysis of regulatory networks on multiple molecular levels. I previously carried out proteomics and metabolomics along with a computational derivation of dynamic protein complexes for IL-3 activation and cell cycle in murine pro-B cells (https://www.cell.com/cell-repo...; see Figure 2 below), for which I developed integrative analytical tools using diverse approaches from machine learning and network theory. My ongoing interests in methodology include machine/deep learning and topological Kolmogorov-Sinai entropy-based network theory, which are applied to (1) multi-level dynamic regulatory networks in immune response, cell cycle, cancer metabolism, and cell fate decision and (2) single cell-based and mass spectrometry-based omics data analysis. Two specific projects were (1) Dynamic metabolic network modeling of a mammalian cell cycle using multi-omics time-course data in collaboration with the Chandrasekaran lab at the University of Michigan (see Figure 3 below; https://www.biorxiv.org/conten...; https://www.cell.com/iscience/...) and (2) Tri-omics analysis of macrophage polarization in pancreatic cancer in collaboration with the Lyssiotis lab at the University of Michigan Medical School (https://elifesciences.org/arti...).

Medical Subject Headings (MeSH)

Algorithms; Artificial Intelligence; Biological Science Disciplines; Chemicals and Drugs; Cheminformatics; Chemistry; Classification; Cloud Computing; Computational Biology; Computer Simulation; Data Science; Diseases; Information Theory; Mathematical Computing; Mathematics; Medical Informatics; Molecular Docking Simulation; Molecular Dynamics Simulation; Multiomics; Organisms; Physics; Signal Processing, Computer-Assisted

Research at a Glance

Yale Co-Authors

Frequent collaborators of Ho-Joon Lee's published research.

Publications

Featured Publications

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Contacts

Locations

  • The Anlyan Center

    Academic Office

    300 Cedar Street, Rm N-212

    New Haven, CT 06519