Dr. Lee is Research Investigator of Molecular and Integrative Physiology. He obtained a Ph.D. in Bioinformatics from the Free University of Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany, and held multiple postdoctoral positions in biophysics, systems biology, systems pharmacology, laboratory medicine, and physiology at Harvard University, Harvard Medical School, Yonsei University School of Medicine, and University of Michigan Medical School. His current research is focused on mass spectrometry-based metabolomics and integrative multi-omics analysis and modeling. He is an affiliated member of Center for Computational Medicine and Bioinformatics (CCMB), Michigan Institute for Data Science (MIDAS), and Rogel Cancer Center.
Areas of Interest
1. Systems-level regulatory networks of cancer immunometabolism, immune activation, and cell cycle
2. Integrative informatics and machine learning of high-dimensional data
3. Methodology development of mass spectrometry-based metabolomics and proteomics
4. Physical principles of molecular networks and evolution
1. Ph.D. in Bioinformatics, Free University of Berlin, Germany, 2008
2. Part III Mathematics, University of Cambridge, UK, 1999
3. M.Sc. in Quantum Fields and Symmetry, Swansea University, UK, 1999
4. B.Sc. in Physics, Yonsei University, Korea, 1997
1. Lee HJ*, Kremer DM, Sajjakulnukit P, Zhang L, Lyssiotis CA*. A large-scale analysis of targeted metabolomics data from heterogeneous biological samples provides insights into metabolite dynamics. Metabolomics (2019). doi.org/10.1007/s11306-019-1564-8.
2. Lee HJ, Jedrychowski MP, Vinayagam A, Wu N, Shyh-Chang N, Hu Y, Min-Wen C, Moore JK, Asara JM, Lyssiotis CA, Perrimon N, Gygi SP, Cantley LC, Kirschner MW. Proteomic and metabolomic characterization of a mammalian cellular transition from quiescence to proliferation. Cell Reports (2017). doi.org/10.1016/j.celrep.2017.06.074.
3. Vinayagam A, Gibson T, Lee HJ, Yilmazel B, Roesel C, Hu Y, Kwon Y, Sharma A, Liu Y-Y, Perrimon N, Barabási A-L. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets. Proc Natl Acad Sci U S A. (2016). doi.org/10.1073/pnas.1603992113.
4. Lee HJ*, Zemojtel T, and Shakhnovich EI. Systems-level evidence of transcriptional co-regulation of yeast protein complexes. Journal of Computational Biology(2009). doi.org/10.1089/cmb.2008.17TT.
* corresponding author