Younghee Lee, Ph.D.

Research Interests

  • Translational Bioinformatics
  • Alternative Splicing
  • Health Disparities
  • Population Genomics
  • Breast Cancer

Languages

  • English
  • Korean

Academic Information

  • Departments: Biomedical Informatics - Assistant Professor

Academic Office Information

  • (801) 581-3673
  • Biomedical Informatics
    421 Wakara Way
    Salt Lake City, UT 84108

Research Statement

For decades, high throughput technologies have successfully captured diverse genome-wide sequence information, quantitative gene expression, and regulatory information. The generation of huge volumes of data by these technologies, ‘omics’ have made remarkable contributions to building a comprehensive list of functional elements in the human genome. We are still learning how to translate these data into biological and clinical knowledge. The primary challenge at hand is determining how to connect genotype with phenotype using those data. Our research contributes to this endeavor by focusing on the study of characterizing the systems-level properties and genetic/molecular basis of human disease by integrating and interpreting genomics and transcriptomics data. Go to http://genomics.chpc.utah.edu

Google Scholar https://scholar.google.com/citations?hl=en&user=pc-yLsYAAAAJ 

Education History

Type School Degree
Postdoctoral Fellowship University of Chicago
Translational Bioinformatics
Postdoctoral Fellow
Doctoral Training Ewha Womans University
Bioinformatics
Ph.D.

Global Impact

Education History

Type School Degree Country
Doctoral Training Ewha Womans University
Bioinformatics
Ph.D. Republic of Korea

Career

Institution Description Country
Center for Cell Signaling Research, Ewha Womans University Research Assistant Republic of Korea
Brain Disease Division, Korea National Institute of Health, Korea Reserach Scientist Republic of Korea

Selected Publications

Journal Article

  1. Differentiation of human pluripotent stem cells to cells similar to cord-blood endothelial colony-forming cells.Prasain N, Lee MR, Vemula S, Meador JL, Yoshimoto M, Ferkowicz MJ, Fett A, Gupta M, Rapp BM, Saadatzadeh MR, Ginsberg M, Elemento O, Lee Y, Voytik-Harbin SL, Chung HM, Hong KS, Reid E, ONeill CL, Medina RJ, Stitt AW, Murphy MP, Rafii S, Broxmeyer HE, Yoder MC (2014). Differentiation of human pluripotent stem cells to cells similar to cord-blood endothelial colony-forming cells. Nat Biotechnol, 32(11), 1151-7.
  2. Network models of genome-wide association studies uncover the topological centrality of protein interactions in complex diseases.Lee Y, Li H, Li J, Rebman E, Achour I, Regan KE, Gamazon ER, Chen JL, Yang XH, Cox NJ, Lussier YA (2013). Network models of genome-wide association studies uncover the topological centrality of protein interactions in complex diseases. J Am Med Inform Assoc, 20(4), 619-29.
  3. Complex-disease networks of trait-associated single-nucleotide polymorphisms (SNPs) unveiled by information theory.Li H, Lee Y, Chen JL, Rebman E, Li J, Lussier YA (2012). Complex-disease networks of trait-associated single-nucleotide polymorphisms (SNPs) unveiled by information theory. J Am Med Inform Assoc, 19(2), 295-305.
  4. Variants affecting exon skipping contribute to complex traits.Lee Y, Gamazon ER, Rebman E, Lee Y, Lee S, Dolan ME, Cox NJ, Lussier YA (2012). Variants affecting exon skipping contribute to complex traits. PLoS Genet, 8(10), e1002998.
  5. Hidden dangers: a cryptic exon disrupts BRCA2 mRNA.Fackenthal JD, Lee Y, Olopade OI (2012). Hidden dangers: a cryptic exon disrupts BRCA2 mRNA. Clin Cancer Res, 18(18), 4865-7.
  6. Biomolecular Systems of Disease Buried Across Multiple GWAS Unveiled by Information Theory and Ontology.Lee Y, Li J, Gamazon E, Chen JL, Tikhomirov A, Cox NJ, Lussier YA (2010). Biomolecular Systems of Disease Buried Across Multiple GWAS Unveiled by Information Theory and Ontology. AMIA Jt Summits Transl Sci Proc, 2010, 31-5.
  7. Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.Lee Y, Yang X, Huang Y, Fan H, Zhang Q, Wu Y, Li J, Hasina R, Cheng C, Lingen MW, Gerstein MB, Weichselbaum RR, Xing HR, Lussier YA (2010). Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. PLoS Comput Biol, 6(4), e1000730.
  8. ECgene: an alternative splicing database update.Lee Y, Lee Y, Kim B, Shin Y, Nam S, Kim P, Kim N, Chung WH, Kim J, Lee S (2007). ECgene: an alternative splicing database update. Nucleic Acids Res, 35(Database issue), D99-103.
  9. ECgene: genome annotation for alternative splicing.Kim P, Kim N, Lee Y, Kim B, Shin Y, Lee S (2005). ECgene: genome annotation for alternative splicing. Nucleic Acids Res, 33(Database issue), D75-9.