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KAIST and Merck Sign MOU to Boost Biotech Innovation
< (From left) KAIST President Kwang-Hyung Lee and Merck CEO Matthias Heinzel >
KAIST (President Kwang-Hyung Lee) signed a Memorandum of Understanding (MOU) with Merck Life Science (CEO Matthias Heinzel) on May 29 to foster innovation and technology creation in advanced biotechnology.
Since May of last year, the two institutions have been discussing multidimensional innovation programs and will now focus on industry-academia cooperation to tackle bioindustry challenges with this MOU as a foundation.
KAIST will conduct joint research projects in various advanced biotechnology fields, such as synthetic biology, mRNA, cell line engineering, and organoids, using the chemical and biological portfolios provided by Merck.
Additionally, KAIST will establish an Experience Lab in collaboration with the Department of Materials Science and Engineering and the Graduate School of Medical Science and Engineering. This lab will support the discovery and analysis of candidate substances in materials science and biology.
Programs to enhance researchers' capabilities will also be offered. Scholarships for graduate students and awards for professors will be implemented. Researchers will have opportunities to participate in global academic events and educational programs hosted by Merck, such as the Curious 2024 Future Insight Conference and the Innovation Cup.
M Ventures, a venture capital subsidiary of Merck Group, will collaborate with KAIST's startup institute to support technology commercialization and continue to develop their startup ecosystem.
The signing ceremony at KAIST's main campus in Daejeon was attended by the CEO of Merck Life Science and the President of KAIST along with representatives from both institutions.
Matthias Heinzel, a member of the Executive Board of Merck and CEO Life Science, said, “This agreement with KAIST is a significant step toward accelerating the development of the life science industry both in Korea and globally. Advancing life science research and fostering the next generation of scientists is essential for discovering new medicines to meet global health needs.”
President Kwang-Hyung Lee responded, “We are pleased to share a vision for scientific advancement with Merck, a leading global technology company. We anticipate that this partnership will strengthen the connection between Merck’s life science business and the global scientific community.”
In March, Merck, a global science and technology company with over 350 years of history, announced a plan to invest 430 billion KRW (€300 million) to build a bioprocessing center in Daejeon, where KAIST is located. This is Merck's largest investment in the Asia-Pacific region.
2024.05.30 View 2831 -
Revolutionary 'scLENS' Unveiled to Decode Complex Single-Cell Genomic Data
Unlocking biological information from complex single-cell genomic data has just become easier and more precise, thanks to the innovative 'scLENS' tool developed by the Biomedical Mathematics Group within the IBS Center for Mathematical and Computational Sciences led by Chief Investigator Jae Kyoung Kim, who is also a professor at KAIST. This new finding represents a significant leap forward in the field of single-cell transcriptomics.
Single-cell genomic analysis is an advanced technique that measures gene expression at the individual cell level, revealing cellular changes and interactions that are not observable with traditional genomic analysis methods. When applied to cancer tissues, this analysis can delineate the composition of diverse cell types within a tumor, providing insights into how cancer progresses and identifying key genes involved during each stage of progression.
Despite the immense potential of single-cell genomic analysis, handling the vast amount of data that it generates has always been challenging. The amount of data covers the expression of tens of thousands of genes across hundreds to thousands of individual cells. This not only results in large datasets but also introduces noise-related distortions, which arise in part due to current measurement limitations.
< Figure 1. Overview of scLENS (single-cell Low-dimensional embedding using the effective Noise Subtract) >
(Left) Current dimensionality reduction methods for scRNA-seq data involve conventional data preprocessing steps, such as log normalization, followed by manual selection of signals from the scaled data. However, this study reveals that the high levels of sparsity and variability in scRNA-seq data can lead to signal distortion during the data preprocessing, compromising the accuracy of downstream analyses.
(Right) To address this issue, the researchers integrated L2 normalization into the conventional preprocessing pipeline, effectively mitigating signal distortion. Moreover, they developed a novel signal detection algorithm that eliminates the need for user intervention by leveraging random matrix theory-based noise filtering and signal robustness testing. By incorporating these techniques, scLENS enables accurate and automated analysis of scRNA-seq data, overcoming the limitations of existing dimensionality reduction methods.
Corresponding author Jae Kyoung Kim highlighted, “There has been a remarkable advancement in experimental technologies for analyzing single-cell transcriptomes over the past decade. However, due to limitations in data analysis methods, there has been a struggle to fully utilize valuable data obtained through extensive cost and time."
Researchers have developed numerous analysis methods over the years to discern biological signals from this noise. However, the accuracy of these methods has been less than satisfactory. A critical issue is that determining signal and noise thresholds often depends on subjective decisions from the users.
The newly developed scLENS tool harnesses Random Matrix Theory and Signal robustness test to automatically differentiate signals from noise without relying on subjective user input.
First author Hyun Kim stated, "Previously, users had to arbitrarily decide the threshold for signal and noise, which compromised the reproducibility of analysis results and introduced subjectivity. scLENS eliminates this problem by automatically detecting signals using only the inherent structure of the data."
During the development of scLENS, researchers identified the fundamental reasons for inaccuracies in existing analysis methods. They found that commonly used data preprocessing methods distort both biological signals and noise. The new preprocessing approach that scLENS offers is free from such distortions.
By resolving issues related to noise threshold determined by subjective user choice and signal distortion in conventional data preprocessing, scLENS significantly outperforms existing methods in accuracy. Additionally, scLENS automates the laborious process of signal dimension selection, allowing researchers to extract biological signals conveniently and automatically.
CI Kim added, "scLENS solves major issues in single-cell transcriptome data analysis, substantially improving the accuracy and efficiency throughout the analysis process. This is a prime example of how fundamental mathematical theories can drive innovation in life sciences research, allowing researchers to more quickly and accurately answer biological questions and uncover secrets of life that were previously hidden."
This research was published in the international journal 'Nature Communications' on April 27.
Terminology
* Single-cell RNA sequencing (scRNA-seq): A technique used to measure gene expression levels in individual cells, providing insights into cell heterogeneity and rare cell types.
* Dimensionality reduction: A method to reduce the number of features or variables in a dataset while preserving the most important information, making data analysis more manageable and interpretable.
* Random matrix theory: A mathematical framework used to model and analyze the properties of large, random matrices, which can be applied to filter out noise in high-dimensional data.
* Signal robustness test: Among the signals, this test selects signals that are robust to the slight perturbation in data because real biological signals should be invariant for such slight modification in the data.
2024.05.09 View 2653 -
KAIST holds its first ‘KAIST Tech Fair’ in New York, USA
< Photo 1. 2023 KAIST Tech Fair in New York >
KAIST (President Kwang-Hyung Lee) announced on the 11th that it will hold the ‘2023 KAIST Tech Fair in New York’ at the Kimmel Center at New York University in Manhattan, USA, on the 22nd of this month. It is an event designed to be the starting point for KAIST to expand its startup ecosystem into the global stage, and it is to attract investments and secure global customers in New York by demonstrating the technological value of KAIST startup companies directly at location.
< Photo 2. President Kwang Hyung Lee at the 2023 KAIST Tech Fair in New York >
KAIST has been holding briefing sessions for technology transfer in Korea every year since 2018, and this year is the first time to hold a tech fair overseas for global companies.
KAIST Institute of Technology Value Creation (Director Sung-Yool Choi) has prepared for this event over the past six months with the Korea International Trade Association (hereinafter KITA, CEO Christopher Koo) to survey customer base and investment companies to conduct market analysis.
Among the companies founded with the technologies developed by the faculty and students of KAIST and their partners, 7 companies were selected to be matched with companies overseas that expressed interests in these technologies. Global multinational companies in the fields of IT, artificial intelligence, environment, logistics, distribution, and retail are participating as demand agencies and are testing the marketability of the start-up's technology as of September.
Daim Research, founded by Professor Young Jae Jang of the Department of Industrial and Systems Engineering, is a company specializing in smart factory automation solutions and is knocking on the door of the global market with a platform technology optimized for automated logistics systems.
< Photo 3. Presentation by Professor Young Jae Jang for DAIM Research >
It is a ‘collaborative intelligence’ solution that maximizes work productivity by having a number of robots used in industrial settings collaborate with one another. The strength of their solution is that logistics robots equipped with AI reinforced learning technology can respond to processes and environmental changes on their own, minimizing maintenance costs and the system can achieve excellent performance even with a small amount of data when it is combined with the digital twin technology the company has developed on its own.
A student startup, ‘Aniai’, is entering the US market, the home of hamburgers, with hamburger patty automation equipments and solutions. This is a robot kitchen startup founded by its CEO Gunpil Hwang, a graduate of KAIST’s School of Electrical Engineering which gathered together the experts in the fields of robot control, design, and artificial intelligence and cognitive technology to develop technology to automatically cook hamburger patties.
At the touch of a button, both sides of the patty are cooked simultaneously for consistent taste and quality according to the set condition. Since it can cook about 200 dishes in an hour, it is attracting attention as a technology that can not only solve manpower shortages but also accelerate the digital transformation of the restaurant industry.
Also, at the tech fair to be held at the Kimmel Center of New York University on the 22nd, the following startups who are currently under market verification in the U.S. will be participating: ▴'TheWaveTalk', which developed a water quality management system that can measure external substances and metal ions by transferring original technology from KAIST; ▴‘VIRNECT’, which helps workers improve their skills by remotely managing industrial sites using XR*; ▴‘Datumo’, a solution that helps process and analyze artificial intelligence big data, ▴‘VESSL AI’, the provider of a solution to eliminate the overhead** of machine learning systems; and ▴ ‘DolbomDream’, which developed an inflatable vest that helps the psychological stability of people with developmental disabilities.
* XR (eXtended Reality): Ultra-realistic technology that enhances immersion by utilizing augmented reality, virtual reality, and mixed reality technologies
** Overhead: Additional time required for stable processing of the program
In addition, two companies (Plasmapp and NotaAI) that are participating in the D-Unicorn program with the support of the Daejeon City and two companies (Enget and ILIAS Biologics) that are receiving support from the Scale Up Tips of the Ministry of SMEs and Startups, three companies (WiPowerOne, IDK Lab, and Artificial Photosynthesis Lab) that are continuing to realize the sustainable development goals for a total of 14 KAIST startups, will hold a corporate information session with about 100 invited guests from global companies and venture capital.
< Photo 4. Presentation for AP Lab >
Prior to this event, participating startups will be visiting the New York Economic Development Corporation and large law firms to receive advice on U.S. government support programs and on their attemps to enter the U.S. market. In addition, the participating companies plan to visit a startup support investment institution pursuing sustainable development goals and the Leslie eLab, New York University's one-stop startup support space, to lay the foundation for KAIST's leap forward in global technology commercialization.
< Photo 5. Sung-Yool Choi, the Director of KAIST Institute of Technology Value Creation (left) at the 2023 KAIST Tech Fair in New York with the key participants >
Sung-Yool Choi, the Director of KAIST Institute of Technology Value Creation, said, “KAIST prepared this event to realize its vision of being a leading university in creating global value.” He added, “We hope that our startups founded with KAIST technology would successfully completed market verification to be successful in securing global demands and in attracting investments for their endeavors.”
2023.09.11 View 9709 -
Image Analysis to Automatically Quantify Gender Bias in Movies
Many commercial films worldwide continue to express womanhood in a stereotypical manner, a recent study using image analysis showed. A KAIST research team developed a novel image analysis method for automatically quantifying the degree of gender bias in films.
The ‘Bechdel Test’ has been the most representative and general method of evaluating gender bias in films. This test indicates the degree of gender bias in a film by measuring how active the presence of women is in a film. A film passes the Bechdel Test if the film (1) has at least two female characters, (2) who talk to each other, and (3) their conversation is not related to the male characters.
However, the Bechdel Test has fundamental limitations regarding the accuracy and practicality of the evaluation. Firstly, the Bechdel Test requires considerable human resources, as it is performed subjectively by a person. More importantly, the Bechdel Test analyzes only a single aspect of the film, the dialogues between characters in the script, and provides only a dichotomous result of passing the test, neglecting the fact that a film is a visual art form reflecting multi-layered and complicated gender bias phenomena. It is also difficult to fully represent today’s various discourse on gender bias, which is much more diverse than in 1985 when the Bechdel Test was first presented.
Inspired by these limitations, a KAIST research team led by Professor Byungjoo Lee from the Graduate School of Culture Technology proposed an advanced system that uses computer vision technology to automatically analyzes the visual information of each frame of the film. This allows the system to more accurately and practically evaluate the degree to which female and male characters are discriminatingly depicted in a film in quantitative terms, and further enables the revealing of gender bias that conventional analysis methods could not yet detect.
Professor Lee and his researchers Ji Yoon Jang and Sangyoon Lee analyzed 40 films from Hollywood and South Korea released between 2017 and 2018. They downsampled the films from 24 to 3 frames per second, and used Microsoft’s Face API facial recognition technology and object detection technology YOLO9000 to verify the details of the characters and their surrounding objects in the scenes.
Using the new system, the team computed eight quantitative indices that describe the representation of a particular gender in the films. They are: emotional diversity, spatial staticity, spatial occupancy, temporal occupancy, mean age, intellectual image, emphasis on appearance, and type and frequency of surrounding objects.
Figure 1. System Diagram
Figure 2. 40 Hollywood and Korean Films Analyzed in the Study
According to the emotional diversity index, the depicted women were found to be more prone to expressing passive emotions, such as sadness, fear, and surprise. In contrast, male characters in the same films were more likely to demonstrate active emotions, such as anger and hatred.
Figure 3. Difference in Emotional Diversity between Female and Male Characters
The type and frequency of surrounding objects index revealed that female characters and automobiles were tracked together only 55.7 % as much as that of male characters, while they were more likely to appear with furniture and in a household, with 123.9% probability.
In cases of temporal occupancy and mean age, female characters appeared less frequently in films than males at the rate of 56%, and were on average younger in 79.1% of the cases. These two indices were especially conspicuous in Korean films.
Professor Lee said, “Our research confirmed that many commercial films depict women from a stereotypical perspective. I hope this result promotes public awareness of the importance of taking prudence when filmmakers create characters in films.”
This study was supported by KAIST College of Liberal Arts and Convergence Science as part of the Venture Research Program for Master’s and PhD Students, and will be presented at the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) on November 11 to be held in Austin, Texas.
Publication:
Ji Yoon Jang, Sangyoon Lee, and Byungjoo Lee. 2019. Quantification of Gender Representation Bias in Commercial Films based on Image Analysis. In Proceedings of the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). ACM, New York, NY, USA, Article 198, 29 pages. https://doi.org/10.1145/3359300
Link to download the full-text paper:
https://files.cargocollective.com/611692/cscw198-jangA--1-.pdf
Profile: Prof. Byungjoo Lee, MD, PhD
byungjoo.lee@kaist.ac.kr
http://kiml.org/
Assistant Professor
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
Profile: Ji Yoon Jang, M.S.
yoone3422@kaist.ac.kr
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
Profile: Sangyoon Lee, M.S. Candidate
sl2820@kaist.ac.kr
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
(END)
2019.10.17 View 22617 -
Professor Jae Kyoung Kim Receives the 2017 HSFP Award
The Human Frontier Science Program (HSFP), one of the most competitive research grants in life sciences, has funded researchers worldwide across and beyond the field since 1990. Each year, the program selects a handful of recipients who push the envelope of basic research in biology to bring breakthroughs from novel approaches. Among its 7,000 recipients thus far, 26 scientists have received the Nobel Prize. For that reason, HSFP grants are often referred to as “Nobel Prize Grants.”
Professor Jae Kyoung Kim of the Mathematical Sciences Department at KAIST and his international collaborators, Professor Robert Havekes from the University of Groningen, the Netherlands, Professor Sara Aton from the University of Michigan in Ann Arbor, the United States, and Professor Matias Zurbriggen from the University of Düsseldorf, Germany, won the Young Investigator Grants of the 2017 HSFP.
The 30 winning teams of the 2017 competition (in 9 Young Investigator Grants and 21 Program Grants) went through a rigorous year-long review process from a total of 1,073 applications submitted from more than 60 countries around the world. Each winning team will receive financial support averaging 110,000-125,000 USD per year for three years.
Although Professor Kim was trained as a mathematician, he has extended his research focus into biological sciences and attempted to solve some of the most difficult problems in biology by employing mathematical theories and applications including nonlinear dynamics, stochastic process, singular perturbation, and parameter estimation.
The project that won the Young Investigator Grants was a study on how a molecular circadian clock may affect sleep-regulated neurophysiology in mammals. Physiological and metabolic processes such as sleep, blood pressure, and hormone secretion exhibit circadian rhythms in mammals. Professor Kim used mathematical modeling and analysis to explain that the mammalian circadian clock is a hierarchical system, in which the master clock in the superchiasmatic nucleus, a tiny region in the brain that controls circadian rhythms, functions as a pacemaker and synchronizer of peripheral clocks to generate coherent systematic rhythms throughout the body.
Professor Kim said, “The mechanisms of our neuronal and hormonal activities regulating many of our bodily functions over a 24-hour cycle are not yet fully known. We go to sleep every night, but do not really know how it affects our brain functions. I hope my experience in mathematics, along with insights from biologists, can find meaningful answers to some of today’s puzzling problems in biological sciences, for example, revealing the complexities of our brains and showing how they work.”
“In the meantime, I hope collaborations between the fields of mathematics and biology, as yet a rare phenomenon in the Korean scientific community, will become more popular in the near future.”
Professor Kim received his doctoral degree in Applied and Interdisciplinary Mathematics in 2013 from the University of Michigan and joined KAIST in 2015. He has published numerous articles in reputable science journals such as Science, Molecular Cell, Proceedings of the National Academy of Sciences, and Nature Communications.
Both the Program Grants and Young Investigator Grants support international teams with members from at least two countries for innovative and creative research. This year, the Program Grants were awarded to research topics ranging from the evolution of counting and the role of extracellular vesicles in breast cancer bone metastasis to the examination of obesity from a mechanobiological point of view.
The Young Investigator Grants are limited to teams that established their independent research within the last five years and received their doctoral degrees within the last decade. Besides Professor Kim’s study, such topics as the use of infrasound for navigation by seabirds and protein formation in photochemistry and photophysics were awarded in 2017.
Full lists of the 2017 HFSP winners are available at: http://www.hfsp.org/awardees/newly-awarded.
About the Human Frontier Science Program (HFSP):
The HFSP is a research funding program implemented by the International Human Frontier Science Program (HFSPO) based in Strasbourg, France. It promotes intercontinental collaboration and training in cutting-edge, interdisciplinary research specializing in life sciences. Founded in 1989, the HFSPO consists of the European Union and 14 other countries including the G7 nations and South Korea.
2017.03.21 View 9025 -
World Renowned Wireless Technology Experts Gathered in KAIST
KAIST hosted the 2015 IEEE WoW from June 5 to 6, 2015
Wireless power transfer technologies, such as wireless electric vehicles, trains and batteries, are increasingly in use. A conference, The 2015 IEEE WoW (Workshop on Wireless Power), was held in KI Building for two days starting June 5, 2015 to exchange ideas on the new trends and issues of the world wireless power technology.
The wireless power conference hosted by Institute of Electrical and Electronics Engineers (IEEE), IEEE WoW, was sponsored by its societies, PELS, IAS, IES, VTS, MAG, and PES.
This year’s conference took place in Korea for the first time and was titled “IEEE PELS Workshop on Emerging Technologies: Wireless Power.” The event was attended by around 200 experts in wireless power from 15 countries to discuss the international standards and current trends.
Keynote speakers were President Don Tan of IEEE; Professor Grant Covic of the University of Auckland; Andrew Daga, the CEO at Momentum Dynamics Corporation; Professor Ron Hui of the City University of Hong Kong; and Jung Goo Cho, the CEO of Green Power Technologies.
The forum included plenary speaking sessions on “The Futures of EV and Power Electronics,” “Development of IPT at the University of Auckland,” “Interoperable Solution for Wireless EV Charging,” “Development of IPT for Factory Automation,” “Commercialization of High Power WPT,” and “WPT: From Directional Power to Omni-directional Power.”
Notably, KAIST Professor Dong-Ho Cho, responsible for KAIST’s On-Line Electric Vehicle (OLEV) development, spoke on “The Development of Shaped Magnetic Field Systems for EVs and Trains” to introduce the KAIST OLEV bus and OLEV trains developed in cooperation with Korea Railroad Research Institute.
The Dialog Sessions on “The Futures of Wireless Electric Vehicles” were led by John M. Miller of JNJ Miller and “Road Charged EV and WPT Regulation and Standard for EV in Japan” by Yoichi Hori of University of Tokyo.
The General Chair of this year’s IEEE WoW, KAIST Professor Chun T. Rim said, “This forum serves a great assistance to the industry using wireless power technology in areas such as smartphones, home appliances, Internet of Things, and wearable devices.”
2015.05.29 View 8226