A research team from KAIST developed a computational framework that enables the reconstruction of a comprehensive computational model of human metabolism, which allows for an accurate prediction of personal metabolic features (or phenotypes). Understanding personal metabolic phenotypes allows us to design effective therapeutic strategies for various chronic and infectious diseases. A human computational model called the genome-scale metabolic model (GEM) contains information on thousands o
2017-10-25A research team led by Professor Sang Ouk Kim in the Department of Materials Science and Engineering at KAIST has developed semiconductor manufacturing technology using a camera flash. This technology can manufacture ultra-fine patterns over a large area by irradiating a single flash with a seven-nanometer patterning technique for semiconductors. It can facilitate the manufacturing of highly efficient, integrated semiconductor devices in the future. Technology for the Artificial In
2017-09-18A KAIST research team presented a novel method for improving medication treatment for liver cancer using Systems Biology, combining research from information technology and the life sciences. Professor Kwang-Hyun Cho in the Department of Bio and Brain Engineering at KAIST conducted the research in collaboration with Professor Jung-Hwan Yoon in the Department of Internal Medicine at Seoul National University Hospital. This research was published in Hepatology in September 2017 (available online f
2017-08-30A KAIST research team led by Professor Ji-Ho Park in the Bio and Brain Engineering Department at KAIST developed a technology for the effective treatment of cancer by delivering synthetic receptors throughout tumor tissue. The study, led by Ph.D. candidate Heegon Kim, was published online in Nature Communications on June 19. Cancer targeted therapy generally refers to therapy targeting specific molecules that are involved in the growth and generation of cancer. The targeted delivery of the
2017-07-07KAIST researchers have established an efficient biocatalytic system to produce terephthalic acid (TPA) from p-xylene (pX). It will allow this industrially important bulk chemical to be made available in a more environmentally-friendly manner. The research team developed metabolically engineered Escherichia coli (E.coli) to biologically transform pX into TPA, a chemical necessary in the manufacturing of polyethylene terephthalate (PET). This biocatalysis system represents a greener and more effi
2017-06-05