Ki-Young Lee, Ph.D.

Affiliations: 
Michigan State University, East Lansing, MI 
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"Ki-Young Lee"

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Hairong Li grad student 2006 Michigan State
 (A dual processing model of virtual experience.)
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Publications

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Eun HJ, Lee KY, Kim DG, et al. (2020) Crystal structure of the YoeB-YefM complex from Staphylococcus aureus. Biochemical and Biophysical Research Communications. 527: 264-269
Kim MJ, Min Y, Im JS, et al. (2020) p62 is Negatively Implicated in the TRAF6-BECN1 Signaling Axis for Autophagy Activation and Cancer Progression by Toll-Like Receptor 4 (TLR4). Cells. 9
Lee KY, Shin KS, Jung JH, et al. (2020) Clinical study on screw loosening in dental implant prostheses: a 6-year retrospective study. Journal of the Korean Association of Oral and Maxillofacial Surgeons. 46: 133-142
Kang TH, Lee SW, Hwang K, et al. (2020) All-Inkjet-Printed Flexible Nanobio-Devices with Efficient Electrochemical Coupling Using Amphiphilic Biomaterials. Acs Applied Materials & Interfaces
Lee KY, Jo S, Tan AJ, et al. (2020) Fast magneto-ionic switching of interface anisotropy using yttria-stabilized zirconia gate oxide. Nano Letters
Yoo M, Chung SH, Park YS, et al. (2020) Clinical Characteristics of Enterocolitis in Korean Adults: A Retrospective Study at a Single Center. The Korean Journal of Gastroenterology = Taehan Sohwagi Hakhoe Chi. 75: 188-197
Lee KY, Lee JH, Kang KC, et al. (2020) Strategy for obtaining solid fusion at L5-S1 in adult spinal deformity: risk factor analysis for nonunion at L5-S1. Journal of Neurosurgery. Spine. 1-9
Choi B, Lee JS, Kim SJ, et al. (2020) Anti-tumor effects of anti-PD-1 antibody, pembrolizumab, in humanized NSG PDX mice xenografted with dedifferentiated liposarcoma. Cancer Letters
Park D, Yoon HJ, Lee KY, et al. (2019) Crystal structure of proteolyzed VapBC and DNA-bound VapBC from Salmonella enterica Typhimurium LT2 and VapC as a putative Ca -dependent ribonuclease. Faseb Journal : Official Publication of the Federation of American Societies For Experimental Biology
Choi A, Jung H, Lee KY, et al. (2019) Machine learning approach to predict center of pressure trajectories in a complete gait cycle: a feedforward neural network vs. LSTM network. Medical & Biological Engineering & Computing
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