Woonghee Lee, Ph.D.
Speaker's Institution
University of Colorado Denver
Chemistry A101
Mixer Time
Mixer Location
Chemistry B101E
Additional Information

About the Seminar

We develop the POKY suite which is the revolutionized platform with boundless possibilities for advancing research and technology development in biomolecular studies. The “POKY” is the core of the Integrative NMR platform providing a fully integrated professional-grade cyberinfrastructure. The next level automation and visualization maximizing the quality of user experience and productivity will be enabled by the `full-stack development’ of artificial intelligence (AI), machine learning (ML), computer vision (CV), and other modern technologies. As well as routine automated studies on well-behaving proteins, it also keeps up with the recent advances in the field such as 13C-detected solution NMR for intrinsically disordered proteins (IDPs) and 1H/13C/19F detected solid-state NMR for large, insoluble and membrane proteins. Different level users will be able to use different interface tools such as step-by-step guided automations (POKY Automation Guide), high-level push buttons (POKY Extensions), intermediate-level Jupyter notebooks (POKY Notebooks), and low-level customizable scripts (POKY Notepad). In this presentation, I will show how POKY makes NMR-based structural studies more accessible and automated with practical examples.


  1. Lee W, Rahimi M, Lee Y, Chiu A. POKY: a software suite for multidimensional NMR and 3D structure calculation of biomolecules. Bioinformatics. 2021 Sep. 15; 37(18):3041-3042.
  2. Rahimi M, Lee Y, Nguyen H, Chiu A, Lee W. A Toolset for the Solid-state NMR-based 3D Structure Calculation of Proteins. Journal of Magnetic Resonance. 2022 June; 339:107214.
  3. Manthey I, Tonelli M, Clos L II, Rahimi M, Markley JL, Lee W. POKY software tools encapsulating assignment strategies for solution and solid-state protein NMR data. Journal of Structural Biology: X. 2022 Aug 28; 6:100073.
  4. Dwarasala A, Rahimi M, Markley JL, Lee W. ssPINE: a probabilistic algorithm for automated chemical shift assignment of solid-state NMR data. Membranes. 2022; 12(9): 834.


About the Speaker

Dr. Woonghee Lee is an Assistant Professor of Chemistry at the University of Colorado Denver (CU Denver). Dr. Lee completed his Ph.D. at the University of Wisconsin-Madison from the Integrated Program in Biochemistry (IPiB) under the guidance of Dr. John Markley after receiving his B.S. and M.S. in Biochemistry from Yonsei University under the guidance of Dr. Weontae Lee. Before joining CU Denver in 2020, Dr. Lee was a principal investigator and a staff scientist at the National Magnetic Resonance Facility At Madison (NMRFAM) after a short postdoctoral training at NMRFAM. Additionally, Dr. Lee was a professional computer programmer for three years at EnGIS technologies developing geographic information system (GIS) programs. Dr. Lee’s unique interdisciplinary background has enabled him to make indispensable components of the NMR research platform considered field standards such as I-PINE and NMRFAM-SPARKY, which are succeeded by the POKY suite.