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Dongwon Lee, Ph.D.

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Biography
education and training
KAIST, Daejeon, South KoreaB.S.08/2007Computer Science
KAIST, Daejeon, South KoreaB.S.08/2007Biological Science
Johns Hopkins University, Baltimore, MD, USAPh.D.03/2013Biomedical Engineering
McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USAPostdoctoral fellow03/2018Human Genetics
Center for Human Genetics & Genomics, New York University School of Medicine, New York, NY, USAPostdoctoral fellow08/2019Human Genetics
awards and honors
2012
TOP 10 Paper Award
2013
Nupur Dinesh Thekdi Award
2015
Top 10 Paper Award
2020
Manton Center Endowed Scholar Award
2020
OFD/BTREC/CTREC Faculty Career Development Fellowship Award
2020
Nephrotic Syndrome Study Network (NEPTUNE) Career Enhancement Award

Overview
overview
Our group studies disease-associated genetic variants using computational approaches with a specific focus on transcriptional regulatory mechanisms. We have developed several machine-learning based methods for predicting regulatory elements and regulatory variants (Lee et al., Nature Genetics 2015). We have shown that these predicted regulatory variants explain a significant proportion of heritability in a tissue-specific manner (Lee et al., Genome Research 2018). Our group will continue to develop computational methods to model regulatory control of human diseases, by incorporating improved machine-learning algorithms and single-cell multi-omic data (genomic, transcriptomic, and epigenomic.) New computational frameworks will help discover the molecular mechanisms driving the development and progression of human diseases.
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Research
research activities and funding
The research activities and funding listed below are automatically derived from NIH ExPORTER and other sources, which might result in incorrect or missing items. Faculty can login to make corrections and additions.
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  1. 1R01HG012871 (Dongwon Lee) May 1, 2023 - Feb 29, 2028
    NIH
    An ensemble framework for regulatory variant prediction
    Role Description: This research proposal aims to develop an improved computational framework to discover non-coding functional variants in the human genome and evaluate their contribution to human diseases in a tissue- and cell-type-resolved manner
    Role: PI
  2. 2R01HL086694 (Aravinda Chakravarti) Apr 1, 2023 - Mar 31, 2027
    NIH
    From GWAS loci to blood pressure genes, variants & mechanisms (FEHGAS4)
    Role: Co-Investigator
  3. 1R01HL158901 (Ashish Kapoor) May 1, 2022 - Apr 30, 2026
    NIH
    Identifying cis-regulatory variants, genes, and regulatory networks underlying QT-interval variation
    Role: Co-Investigator
  4. RC2DK122397 (HILDEBRANDT, FRIEDHELM ;POLLAK, MARTIN R. ;SAMPSON, MATTHEW GORDON;SANNA-CHERCHI, SIMONE) Aug 15, 2020 - May 31, 2025
    NIH
    Integrating large scale genomics and functional studies to accelerate FSGS/NS discovery
    Role Description: The four lead investigators of this project have assembled ~10,000 patients with focal and segmental glomerulosclerosis (FSGS) and steroid-resistant nephrotic syndrome (SRNS). We will use this large cohort and new analytic methods to address major gaps in understanding the genetic basis of FSGS and NS.
    Role: Co-Investigator
  5. R01DK119380 (SAMPSON, MATTHEW GORDON) Sep 18, 2019 - Aug 31, 2024
    NIH
    Whole Genome Sequencing for Nephrotic Syndrome Discovery
    Role: Co-Investigator

Bibliographic
selected publications
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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© 2024 President and Fellows of Harvard College
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.