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Prof. Kwang-Hyun Cho of Department of Bio and Brain Engineering at KAIST has been recently elected editor-in-chief of the Systems Biology, an international journal published by the London-based Institution of Engineering and Technology (IET), the university authorities said on Wednesday (Sept. 23)
By the year 2012, Cho will oversee the editorial process of the journal covering intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. IET, one of the world"s leading professional societies for the engineering and technology community, has a worldwide membership of more than 150,000.
Prof. Cho"s research interests cover the areas of systems science with bio-medical applications including systems biology and bio-inspired engineering based on molecular systems biology. He is currently an editorial board member of Systems and Synthetic Biology (Springer, Netherlands, from 2006), BMC Systems Biology (BMC, London, U.K., from 2007), Gene Regulation and Systems Biology (Libertas Academica, New Zealand, from 2007), and Bulletin of Mathematical Biology (Springer, New York, from 2008), and an editorial advisory board member of Molecular BioSystems (The Royal Society of Chemistry, U.K.).
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research A KAIST Research Team Identifies a Cancer Reversion Mechanism
Despite decades of intensive cancer research by numerous biomedical scientists, cancer still holds its place as the number one cause of death in Korea. The fundamental reason behind the limitations of current cancer treatment methods is the fact that they all aim to completely destroy cancer cells, which eventually allows the cancer cells to acquire immunity. In other words, recurrences and side-effects caused by the destruction of healthy cells are inevitable. To this end, some have suggested a
2023-06-20 -
research Connecting the Dots to Find New Treatments for Breast Cancer
Systems biologists uncovered new ways of cancer cell reprogramming to treat drug-resistant cancers Scientists at KAIST believe they may have found a way to reverse an aggressive, treatment-resistant type of breast cancer into a less dangerous kind that responds well to treatment. The study involved the use of mathematical models to untangle the complex genetic and molecular interactions that occur in the two types of breast cancer, but could be extended to find ways for treating many others.
2021-12-07 -
research 3D Visualization and Quantification of Bioplastic PHA in a Living Bacterial Cell
3D holographic microscopy leads to in-depth analysis of bacterial cells accumulating the bacterial bioplastic, polyhydroxyalkanoate (PHA) A research team at KAIST has observed how bioplastic granule is being accumulated in living bacteria cells through 3D holographic microscopy. Their 3D imaging and quantitative analysis of the bioplastic ‘polyhydroxyalkanoate’ (PHA) via optical diffraction tomography provides insights into biosynthesizing sustainable substitutes for petroleum-bas
2021-07-28 -
research E. coli Engineered to Grow on CO₂ and Formic Acid as Sole Carbon Sources
- An E. coli strain that can grow to a relatively high cell density solely on CO₂ and formic acid was developed by employing metabolic engineering. - Most biorefinery processes have relied on the use of biomass as a raw material for the production of chemicals and materials. Even though the use of CO₂ as a carbon source in biorefineries is desirable, it has not been possible to make common microbial strains such as E. coli grow on CO₂. Now, a metabolic engineering research group at KAIST ha
2020-09-29 -
research Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions
(Figure: Overall scheme of DeepEC) A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions. A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precisio
2019-07-09