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Professor Won-Ki Cho Selected as the 2020 SUHF Young Investigator
Professor Won-Ki Cho from the Department of Biological Sciences was named one of three recipients of the 2020 Suh Kyung-Bae Science Foundation (SUHF) Young Investigator Award.
The SUHF is a non-profit organization established in 2016 and funded by a personal donation of 300 billion KRW in shares from Chairman and CEO Kyung-Bae Suh of the Amorepacific Group. The primary purpose of the foundation is to serve as a platform to nurture and provide comprehensive long-term support for creative and passionate young Korean scientists committed to pursuing research in the field of life sciences. The SUHF selects three to five scientists through an open recruiting process every year and grants each scientist a maximum of 2.5 billion KRW over a period of up to five years.
Since January this year, the foundation received 67 research proposals from scientists across the nation, especially from those who had less than five years of experience as professors, and selected the three recipients.
Professor Cho proposed research on how to observe the interactions between nuclear structures and constantly-changing chromatin monomers in four dimensions through ultra-high-resolution imaging of single living cells. This proposal was recognized as one that could help us better understand the process of transcription regulation, which remains a long-standing question in biology.
The other awards were given to Professor Soung-hun Roh of Seoul National University and Professor Joo-Hyeon Lee of the University of Cambridge.
With these three new awardees, a total of 17 scientists have been named SUHF Young Investigators to date, and the funding to support these scientists now totals 42.5 billion KRW.
Professor Inkyung Jung and Professor Ki-Jun Yoon from the Department of Biological Sciences, and Professor Young Seok Ju and Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering are the four previous winners from KAIST in the years 2017 through 2019.
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2020.10.15 View 12761 -
Big Ideas on Emerging Materials Explored at EMS
Renowned scholars and editors from academic journals joined the Emerging Materials e-Symposium (EMS) held at KAIST and shared the latest breakthroughs and big ideas in new material development last month. This e-symposium was organized by Professor Il-Doo Kim from the KAIST Department of Materials Sciences and Engineering over five days from September 21 through 25 via Zoom and YouTube. Professor Kim also serves as an associate editor of ACS Nano.
Esteemed scholars and editors of academic journals including ACS Nano, Nano Energy, and Energy Storage Materials made Zoom presentations in three main categories: 1) nanostructures for next-generation applications, 2) chemistry and biotechnology for applications in the fields of environment and industry, and 3) material innovation for technological applications.
During Session I, speakers including Professor John A. Rogers of Northwestern University and Professor Zhenan Bao of Stanford University led the session on Emerging Soft Electronics and 3D printing.
In later sessions, other globally recognized scholars gave talks titled Advanced Nanostructuring for Emerging Materials, Frontiers in Emerging Materials Research, Advanced Energy Materials and Functional Nanomaterials, and Latest Advances in Nanomaterials Research.
These included 2010 Nobel Prize laureate and professor at Manchester University Andre Geim, editor-in-chief of ACS Nano and professor at UCLA Paul S. Weiss, Professor Paul Alivisatos of UC Berkeley, Professor William Chueh of Stanford University, and Professor Mircea Dinca of MIT.
KAIST President Sung-Chul Shin, who is also a materials physicist, said in his opening address, “Innovation in materials science will become an important driving force to change our way of life. All the breakthroughs in materials have extended a new paradigm that has transformed our lives.”
“Creative research projects alongside global collaborators like all of you will allow the breakthroughs that will deliver us from these crises,” he added.
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2020.10.06 View 14380 -
PhD Graduate Mekuria Teklemariam Inspired to Better Serve Ethiopia
Ethiopia’s Former Minister of Urban Development and Housing Mekuria Teklemariam became a KAIST alumnus, earning his PhD in the Global IT Technology Program (ITTP) last month. Dr. Telkemariam completed his degree summa cum laude in business administration in four years. He is the highest-ranking official among the ITTP Program recipients.
Dr. Teklemarian cited the ‘Saemaul Undong,’ also known as the New Community Movement as well as the strong infrastructure of IT industry as part of the driving forces behind Korea’s rapid economic success and this inspired him to choose KAIST as his academic destination.
The Global ITTP was launched in 2006 to educate elite public officials from diverse countries on information and communication technology. This program has played a vital role in transferring Korea’s advanced information and communications technology to many countries whose industries are in the budding stages.
Approximately 200 officials from over 50 countries have enrolled in the ITTP program, and the program has expanded to cover diverse areas of ICT and grown into a global network of ICT leaders abroad. The 2020 Class graduated five PhDs and five master’s degree holders.
Dr. Teklemariam plans to benchmark Korea to aid the development of Ethiopia when he returns home. “Korea is a country that has made remarkable progress in all areas including politics and economics in the last few decades, emerged from one of the poorest countries in the 1960s to be among the largest economies in the world today,” Dr. Telkemariam said.
“So I wanted to study what transformed Korea to make such a miraculous transformation academically for my country’s own development too,” he added, explaining his motivation to study in Korea. He also cited diverse IT education programs for the elderly as a Korean policy he would like to see applied in his country.
The 50-year-old former minister and incumbent urban affairs advisor to the prime minister of Ethiopia was elected to the country's parliament a decade ago, becoming the youngest member in Ethiopian history. He has led the economic development of Ethiopia in the areas of smart city development, land management, and housing development policies.
While studying at KAIST, Dr. Telkemariam became the two-time winner of the Outstanding Collaborative Research Award presented by the KAIST Institute for IT Convergence through collaborative research with the National IT Industry Promotion Agency (NIPA) and the Science and Technology Policy Institute (STEPI).
In addition, his graduation thesis, "Differentiating mobile broadband policies across diffusion stages: A panel data analysis" was published in Telecommunications Policy.
President Sung-Chul Shin met with him during a luncheon meeting before he returned to home. During the meeting Dr. Telkemariam said, “I was impressed by the Korean people, who not only work hard to do their part wherever they are, but also put whatever they say into practice. I will apply and practice what I have learned from Korea and KAIST to Ethiopia.” President Shin responded, “We shall seek to find ways to cooperate that can be practically used to expand exchanges between the two countries.”
2020.09.21 View 7386 -
Life After COVID-19: Big Questions on Medical and Bio-Engineering
KAIST GSI forum explores big questions in the medical and bio-engineering revolution caused by the COVID-19 in fight against infectious diseases and life quality
On September 9, the Global Strategy Institute at KAIST will delve into innovative future strategies for the medical and bio-engineering sectors that have been disrupted by COVID-19. The forum will live stream via YouTube, KTV, and Naver TV from 9:00 am Korean time.
The online forum features a speaker lineup of world-renowned scholars who will discuss an array of bio-engineering technologies that will improve our quality of life and even extend our life span. This is the GSI’s third online forum since the first one in April that covered the socio-economic implications of the global pandemic and the second one in June focusing on the education sector.
In hosting the third round of the GSI Forum series, KAIST President Sung-Chul Shin stressed the power of science and technology saying, “In this world full of uncertainties, one thing for sure is that only the advancement of science and technology will deliver us from this crisis.” Korean Prime Minister Sye-Kyun Chung will also deliver a speech explaining the government’s response to COVID-19 and vaccine development strategies.
The President of the National Academy of Medicine in the US will share ideal policies to back up the bio-engineering and medical sectors and Futurist Thomas Frey from the Davinci Institute will present his distinct perspectives on our future lives after COVID-19. His thought-provoking insights on advancements in the bioengineering sector will examine whether humanity can put an end to infectious diseases and find new ways to lengthen our lives.
Two distinguished professors in the field of genetic engineering technology will share their latest breakthroughs. Professor George McDonald Church from Harvard Medical School who developed genome sequencing will deliver a keynote speech on how the advancement of gene editing and genome technology will overcome diseases and contribute to extending human life spans.
Professor Kwang-Soo Kim, a KAIST alumnus from Harvard Medical School who recently reported new discoveries for Parkinson’s disease treatment by reprogramming a patient’s own skin cells to replace cells in the brain, will introduce the latest clinical cell treatment technologies based on personalized therapeutics.
Senior Vice President and Chief Product Officer of Illumina Susan Tousi, a leading genome sequencing solution provider, will describe genome analysis technology and explore the potential for disease prevention.
KAIST medical scientist Jeong Ho Lee, who was the first to identify the causes of intractable epilepsies and has identified the genes responsible for several developmental brain disorders. Professor Jin-Hyung Lee from Stanford University and Dr. David B. Resnik from the National Institute of Environmental Health Science will also join the speaker lineup to discuss genetics-based personalized solutions to extend human life spans.
The forum will also invite about 50 young scientists and medical researchers from around the world to participate in an online panel session. They will engage in a Q&A session and a discussion with the speakers.
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2020.09.04 View 10170 -
Before Eyes Open, They Get Ready to See
- Spontaneous retinal waves can generate long-range horizontal connectivity in visual cortex. -
A KAIST research team’s computational simulations demonstrated that the waves of spontaneous neural activity in the retinas of still-closed eyes in mammals develop long-range horizontal connections in the visual cortex during early developmental stages.
This new finding featured in the August 19 edition of Journal of Neuroscience as a cover article has resolved a long-standing puzzle for understanding visual neuroscience regarding the early organization of functional architectures in the mammalian visual cortex before eye-opening, especially the long-range horizontal connectivity known as “feature-specific” circuitry.
To prepare the animal to see when its eyes open, neural circuits in the brain’s visual system must begin developing earlier. However, the proper development of many brain regions involved in vision generally requires sensory input through the eyes.
In the primary visual cortex of the higher mammalian taxa, cortical neurons of similar functional tuning to a visual feature are linked together by long-range horizontal circuits that play a crucial role in visual information processing.
Surprisingly, these long-range horizontal connections in the primary visual cortex of higher mammals emerge before the onset of sensory experience, and the mechanism underlying this phenomenon has remained elusive.
To investigate this mechanism, a group of researchers led by Professor Se-Bum Paik from the Department of Bio and Brain Engineering at KAIST implemented computational simulations of early visual pathways using data obtained from the retinal circuits in young animals before eye-opening, including cats, monkeys, and mice.
From these simulations, the researchers found that spontaneous waves propagating in ON and OFF retinal mosaics can initialize the wiring of long-range horizontal connections by selectively co-activating cortical neurons of similar functional tuning, whereas equivalent random activities cannot induce such organizations.
The simulations also showed that emerged long-range horizontal connections can induce the patterned cortical activities, matching the topography of underlying functional maps even in salt-and-pepper type organizations observed in rodents. This result implies that the model developed by Professor Paik and his group can provide a universal principle for the developmental mechanism of long-range horizontal connections in both higher mammals as well as rodents.
Professor Paik said, “Our model provides a deeper understanding of how the functional architectures in the visual cortex can originate from the spatial organization of the periphery, without sensory experience during early developmental periods.”
He continued, “We believe that our findings will be of great interest to scientists working in a wide range of fields such as neuroscience, vision science, and developmental biology.”
This work was supported by the National Research Foundation of Korea (NRF). Undergraduate student Jinwoo Kim participated in this research project and presented the findings as the lead author as part of the Undergraduate Research Participation (URP) Program at KAIST.
Figures and image credit: Professor Se-Bum Paik, KAIST
Image usage restrictions: News organizations may use or redistribute these figures and image, with proper attribution, as part of news coverage of this paper only.
Publication:
Jinwoo Kim, Min Song, and Se-Bum Paik. (2020). Spontaneous retinal waves generate long-range horizontal connectivity in visual cortex. Journal of Neuroscience, Available online athttps://www.jneurosci.org/content/early/2020/07/17/JNEUROSCI.0649-20.2020
Profile: Se-Bum Paik
Assistant Professor
sbpaik@kaist.ac.kr
http://vs.kaist.ac.kr/
VSNN Laboratory
Department of Bio and Brain Engineering
Program of Brain and Cognitive Engineering
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea
Profile: Jinwoo Kim
Undergraduate Student
bugkjw@kaist.ac.kr
Department of Bio and Brain Engineering, KAIST
Profile: Min Song
Ph.D. Candidate
night@kaist.ac.kr
Program of Brain and Cognitive Engineering, KAIST
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2020.08.25 View 12381 -
Professor Jaehyouk Choi, IT Young Engineer of the Year
Professor Jaehyouk Choi from the KAIST School of Electrical Engineering won the ‘IT Young Engineer Award’ for 2020. The award was co-presented by the Institute of Electrical and Electronics Engineers (IEEE) and the Institute of Electronics Engineers of Korea (IEIE), and sponsored by the Haedong Science and Culture Foundation.
The ‘IT Young Engineer Award’ selects only one mid-career scientist or engineer 40 years old or younger every year, who has made a great contribution to academic or technological advancements in the field of IT.
Professor Choi’s research topics include high-performance semiconductor circuit design for ultrahigh-speed communication systems including 5G communication. In particular, he is widely known for his field of the ‘ultra-low-noise, high-frequency signal generation circuit,’ key technology for next-generation wired and wireless communications, as well as for memory systems. He has published 64 papers in SCI journals and at international conferences, and applied for and registered 25 domestic and international patents.
Professor Choi is also an active member of the Technical Program Committee of international symposiums in the field of semiconductor circuits including the International Solid-State Circuits Conference (ISSCC) and the European Solid-State Circuit Conference (ESSCIRC). Beginning this year, he also serves as a distinguished lecturer at the IEEE Solid-State Circuit Society (SSCS).
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2020.08.20 View 10925 -
KAIST Technology Value Tops in Commercialization Market
KAIST became the first Korean university to achieve 10.183 billion KRW in annual technology royalties, and was also selected as an ‘Institution of Outstanding Patent Quality Management’ and an ‘Institution of Outstanding Public Patent Technology Transfer’ for 2020.
KAIST earns its technology royalties through 56 technology transfer contracts. Following KAIST in the rankings were Seoul National University (SNU) in second place with 8.8 billion KRW from 87 contracts and Korea University (KU) in the third with 5.4 billion KRW from 133 contracts. The data shows the high value of KAIST-created technology in the market.
The Korean Intellectual Property Office (KIPO) started to recognize the Institution of Outstanding Patent Quality Management this year to encourage profit-driven patent management at universities and public research institutes, and KAIST was selected as one of the four first recipients of this distinction.
In addition, KAIST was selected as an Institution of Outstanding Public Patent Technology Transfer, a title given by KIPO to three universities and public research institutes this year with outstanding achievements in technology transfers and commercialization to encourage patent utilization.
Director of the KAIST Institute of Technology Value Creation (ITVC) Professor Kyung-cheol Choi said that KAIST’s achievement in annual technology royalties and technology transfers and commercialization were prime examples of accelerating competitiveness in intellectual property through innovative R&D investment.
In April, KAIST expanded and reorganized its Industry-Academia Collaboration Team into the ITVC to support technology transfers and commercialization. Specialized organizations such as the Intellectual Property and Technology Transfer Center and Industrial Liaison Center have been established under the ITVC, and industry experts have been recruited as special professors focusing on industry-academia collaborations to enhance its specialized functions.
KAIST also operates an enterprise membership system and technology consulting system, aimed at sharing its outstanding intellectual property within domestic industries. In 2019, it secured a technology transfer commercialization fund of 1.2 billion KRW available for three years under KIPO’s Intellectual Property Profit Reinvestment Support Program (formerly the Korean Patent Gap Fund Creation Project).
This program was introduced to bridge the gap between the technology developed in universities and the level of technology required by industry. Under the program, bold investments are made in early-stage technologies at the research paper or experiment phase.
The program encourages enterprises to take active steps for the transfer of technologies by demonstrating their commercial potential through prototype production, testing and certification, and standard patent filing. KAIST is currently funding approximately 20 new technologies under this program as of July 2020.
KAIST’s outstanding intellectual property management has also received international recognition, with its selection as Asia’s leading institution in university R&D intellectual property at the Intellectual Property Business Congress (IPBC) Asia 2019 held in Tokyo, Japan last October.
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2020.08.18 View 9805 -
Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time
The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis.
Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %.
Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room.
Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image.
To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else.
In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places.
The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances.
The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment.
In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer.
The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image.
A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms.
Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient's condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff."
This study was conducted in collaboration with SM Instruments Inc.
Profile: Yong-Hwa Park, Ph.D.
Associate Professor
yhpark@kaist.ac.kr
http://human.kaist.ac.kr/
Human-Machine Interaction Laboratory (HuMaN Lab.)
Department of Mechanical Engineering (ME)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr/en/
Daejeon 34141, Korea
Profile: Gyeong Tae Lee
PhD Candidate
hansaram@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Seong Hu Kim
PhD Candidate
tjdgnkim@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Hyeonuk Nam
PhD Candidate
frednam@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Young-Key Kim
CEO
sales@smins.co.kr
http://en.smins.co.kr/
SM Instruments Inc.
Daejeon 34109, Korea
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2020.08.13 View 15775 -
KAIST Receives $57 Million Donation to Enhance Research
The largest amount since the opening of KAIST will fund ‘Singularity Professors’
KAIST Development Foundation Chairman Soo-Young Lee made a gift of real estate estimated at approximately $57 million on July 23. This is the largest donation KAIST has received since it was founded in 1971.
The fund will establish the “Soo-Young Lee Science Education Foundation” and the proceeds of the foundation will go to the “Singularity Professors” as necessary resources to help make discoveries and design new approaches to accelerate breakthroughs.
“KAIST should be the institute that will produce first Korean Nobel laureate in the field of science. I hope this fund will be utilized to enable Korea to stand out in this challenging time by accomplishing breakthroughs nobody has never imagined,” said Chairman Lee during the donation ceremony at KAIST’s campus in Daejeon.
This is Chairman Lee’s third donation following the $6.7 million donation in 2012 and the $830,000 donation in 2016. Chairman Lee began her career as a journalist in 1963. In 1981, she started her own business by launching Kwangwon Ranch and became a successful businesswoman. In 1988, Chairman Lee established the real estate company Kwangwon Industries. After receiving an honorary doctorate from KAIST in 2012, she has served as the chairman of the KAIST Development Foundation from 2013. Chairman Lee expressed her intention to make another donation to KAIST in the near future during the news conference.
“People matter most for advancing the world. KAIST has a very distinct mission to foster the brightest minds and will drive the nation to move forward. I have worked with KAIST for quite long time so that I have a strong belief that KAIST is the one that will not only make contributions to Korea but also to all humanity,” she explained.
“For example, about one-fourth of the R&D manpower at Samsung Electronics is from KAIST. In 2019, Samsung Electronics recorded a revenue of approximately $206 billion which accounted for about 16% of national GDP. KAIST is the one that fosters global talents who are working at global company such as Samsung and many others.”
KAIST President Sung-Chul Shin also expressed his deep respect for Chairman Lee’s decision, saying that the entire KAIST community will make every effort to keep up Chairman Lee’s noble idea encouraging KAIST to push forward and help realize KAIST’s role and mission.
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2020.07.23 View 8682 -
Singularity Professors Represent the Future of Research at KAIST
KAIST will launch a Singularity Professor track, which gives more freedom to researchers for pursuing their research goal. This more flexible and creative research environment institutionally supports researchers as they dive deeper into their research for a longer period of time without any strings attached.
The track was established in an effort to ensure more competitive researchers who can lead the way for new advances in science and technology. This innovative research initiative is part of KAIST’s expansive effort to envision and position itself to build global research competitiveness in the wake of its 50th anniversary in 2021 and beyond.
From this year, KAIST will select two to three research faculty for this special track with full-scale funding for 10 years. Singularity Professors will have their annual performance evaluations waived for 10 years. Instead, their research will be reviewed in their fifth year. The professors in this track will not participate in government-funded R&D projects and be fully funded by KAIST’s endowment.
In addition to those newly hired into this track, Singularity Professorships are opens to existing faculty members. The selection criteria are very simple but highly demanding: one who can pivot an existing academic paradigm or invent a new discipline by presenting a novel scientific theory.
KAIST recently hosted a briefing session for current faculty members and encouraged them to apply for the new track. As part of the selection criteria, the research topic’s innovativeness, feasibility, and appropriateness will be major factors for this track. Employment under this track will continue for up to 20 years. After receiving an evaluation of Very Satisfactory at the end of first ten-year contract, another ten years will be added.
President Sung-Chul Shin, who has pushed for this system since he took office in 2017, said during the briefing session, “It takes quite a long time to bear fruit in academics, especially in science. I am very delighted that KAIST is paving the way for building a longer-term research environment which allows full and longer commitments for research that the faculty is excited to try. That’s the first step to sow the seeds for bearing fruit in academics, especially in science.”
This is a paradigm shift to embrace transformation in a new era. The new institutional strategy supports the change from a fast follower to a first mover during these technologically turbulent times. Under its Global Singularity Research Projects initiative, KAIST already selected focus research topics in the most challenging as well as most creative fields of neuro-rehabilitation, new materials, and molecular optogenetics.
“Especially in the post-COVID era, we have a very clear mission for the world. Our knowledge should translate into global value that can benefit those suffering from this pandemic, and mitigate the inequity coming from the digital discrepancies,” President Shin added.
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2020.07.21 View 8456 -
X-ray Scattering Shines Light on Protein Folding
- Multiple forms of a non-functional, unfolded protein follow different pathways and timelines to reach its folded, functional state, a study reveals. -
KAIST researchers have used an X-ray method to track how proteins fold, which could improve computer simulations of this process, with implications for understanding diseases and improving drug discovery. Their findings were reported in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 30.
When proteins are translated from their DNA codes, they quickly transform from a non-functional, unfolded state into their folded, functional state. Problems in folding can lead to diseases like Alzheimer’s and Parkinson’s.
“Protein folding is one of the most important biological processes, as it forms the functioning 3D protein structure,” explained the physical chemist Hyotcherl Ihee of the Department of Chemistry at KAIST. Dr. Tae Wu Kim, the lead author of this research from Ihee’s group, added, “Understanding the mechanisms of protein folding is important, and could pave the way for disease study and drug development.”
Ihee’s team developed an approach using an X-ray scattering technique to uncover how the protein cytochrome c folds from its initial unfolded state. This protein is composed of a chain of 104 amino acids with an iron-containing heme molecule. It is often used for protein folding studies.
The researchers placed the protein in a solution and shined ultraviolet light on it. This process provides electrons to cytochrome c, reducing the iron within it from the ferric to the ferrous form, which initiates folding. As this was happening, the researchers beamed X-rays at very short intervals onto the sample. The X-rays scattered off all the atomic pairs in the sample and a detector continuously recorded the X-ray scattering patterns. The X-ray scattering patterns provided direct information regarding the 3D protein structure and the changes made in these patterns over time showed real-time motion of the protein during the folding process.
The team found cytochrome c proteins initially exist in a wide variety of unfolded states. Once the folding process is triggered, they stop by a group of intermediates within 31.6 microseconds, and then those intermediates follow different pathways with different folding times to reach an energetically stable folded state.
“We don’t know if this diversity in folding paths can be generalized to other proteins,” Ihee confessed. He continued, “However, we believe that our approach can be used to study other protein folding systems.”
Ihee hopes this approach can improve the accuracy of models that simulate protein interactions by including information on their unstructured states. These simulations are important as they can help identify barriers to proper folding and predict a protein’s folded state given its amino acid sequence. Ultimately, the models could help clarify how some diseases develop and how drugs interact with various protein structures.
Ihee’s group collaborated with Professor Young Min Rhee at the KAIST Department of Chemistry, and this work was supported by the National Research Foundation of Korea (NRF) and the Institute for Basic Science (IBS).
Figure. The scientists found that non-functional unfolded forms of the protein cytochrome c follow different pathways and timelines to reach a stable functional folded state.
Publications:
Kim, T. W., et al. (2020) ‘Protein folding from heterogeneous unfolded state revealed by time-resolved X-ray solution scattering’. PNAS. Volume 117. Issue 26. Page 14996-15005. Available online at https://doi.org/10.1073/pnas.1913442117
Profile: Hyotcherl Ihee, Ph.D.
Professor
hyotcherl.ihee@kaist.ac.kr
http://time.kaist.ac.kr/
Ihee Laboratory
Department of Chemistry
KAIST
https://www.kaist.ac.kr
Daejeon 34141, Korea
Profile: Young Min Rhee, Ph.D.
Professor
ymrhee@kaist.ac.kr
http://singlet.kaist.ac.kr
Rhee Research Group
Department of Chemistry
KAIST
https://www.kaist.ac.kr
Daejeon 34141, Korea
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2020.07.09 View 14464 -
Quantum Classifiers with Tailored Quantum Kernel
Quantum information scientists have introduced a new method for machine learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new insights for improving the accuracy of quantum machine learning, deemed able to outperform the current AI technology.
The research team led by Professor June-Koo Kevin Rhee from the School of Electrical Engineering, proposed a quantum classifier based on quantum state fidelity by using a different initial state and replacing the Hadamard classification with a swap test. Unlike the conventional approach, this method is expected to significantly enhance the classification tasks when the training dataset is small, by exploiting the quantum advantage in finding non-linear features in a large feature space.
Quantum machine learning holds promise as one of the imperative applications for quantum computing. In machine learning, one fundamental problem for a wide range of applications is classification, a task needed for recognizing patterns in labeled training data in order to assign a label to new, previously unseen data; and the kernel method has been an invaluable classification tool for identifying non-linear relationships in complex data.
More recently, the kernel method has been introduced in quantum machine learning with great success. The ability of quantum computers to efficiently access and manipulate data in the quantum feature space can open opportunities for quantum techniques to enhance various existing machine learning methods.
The idea of the classification algorithm with a nonlinear kernel is that given a quantum test state, the protocol calculates the weighted power sum of the fidelities of quantum data in quantum parallel via a swap-test circuit followed by two single-qubit measurements (see Figure 1). This requires only a small number of quantum data operations regardless of the size of data. The novelty of this approach lies in the fact that labeled training data can be densely packed into a quantum state and then compared to the test data.
The KAIST team, in collaboration with researchers from the University of KwaZulu-Natal (UKZN) in South Africa and Data Cybernetics in Germany, has further advanced the rapidly evolving field of quantum machine learning by introducing quantum classifiers with tailored quantum kernels.This study was reported at npj Quantum Information in May.
The input data is either represented by classical data via a quantum feature map or intrinsic quantum data, and the classification is based on the kernel function that measures the closeness of the test data to training data.
Dr. Daniel Park at KAIST, one of the lead authors of this research, said that the quantum kernel can be tailored systematically to an arbitrary power sum, which makes it an excellent candidate for real-world applications.
Professor Rhee said that quantum forking, a technique that was invented by the team previously, makes it possible to start the protocol from scratch, even when all the labeled training data and the test data are independently encoded in separate qubits.
Professor Francesco Petruccione from UKZN explained, “The state fidelity of two quantum states includes the imaginary parts of the probability amplitudes, which enables use of the full quantum feature space.”
To demonstrate the usefulness of the classification protocol, Carsten Blank from Data Cybernetics implemented the classifier and compared classical simulations using the five-qubit IBM quantum computer that is freely available to public users via cloud service. “This is a promising sign that the field is progressing,” Blank noted.
Link to download the full-text paper:
https://www.nature.com/articles/s41534-020-0272-6
-Profile
Professor June-Koo Kevin Rhee
rhee.jk@kaist.ac.kr
Professor, School of Electrical Engineering
Director, ITRC of Quantum Computing for AIKAIST
Daniel Kyungdeock Parkkpark10@kaist.ac.krResearch Assistant ProfessorSchool of Electrical EngineeringKAIST
2020.07.07 View 11806