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1,058 results on '"Kim, Ji-Hun"'

17. System-Level Analysis of Transcriptional and Translational Regulatory Elements in Streptomyces griseus

Author

Hwang, Soonkyu, Lee, Namil, Choe, Donghui, Lee, Yongjae, Kim, Woori, Kim, Ji Hun, Kim, Gahyeon, Kim, Hyeseong, Ahn, Neung-Ho, Lee, Byoung-Hee, Palsson, Bernhard O, and Cho, Byung-Kwan

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Streptomyces, differential gene expression, regulatory elements, sigma factor, transcription factor, transcript 3 '-end positions, transcript 3′-end positions, Other Biological Sciences, Biomedical Engineering, Medical Biotechnology, Industrial biotechnology, Medical biotechnology, Biomedical engineering
Abstract

Bacteria belonging to Streptomyces have the ability to produce a wide range of secondary metabolites through a shift from primary to secondary metabolism regulated by complex networks activated after vegetative growth terminates. Despite considerable effort to understand the regulatory elements governing gene expression related to primary and secondary metabolism in Streptomyces, system-level information remains limited. In this study, we integrated four multi-omics datasets from Streptomyces griseus NBRC 13350: RNA-seq, ribosome profiling, dRNA-seq, and Term-Seq, to analyze the regulatory elements of transcription and translation of differentially expressed genes during cell growth. With the functional enrichment of gene expression in different growth phases, one sigma factor regulon and four transcription factor regulons governing differential gene transcription patterns were found. In addition, the regulatory elements of transcription termination and post-transcriptional processing at transcript 3'-end positions were elucidated, including their conserved motifs, stem-loop RNA structures, and non-terminal locations within the polycistronic operons, and the potential regulatory elements of translation initiation and elongation such as 5'-UTR length, RNA structures at ribosome-bound sites, and codon usage were investigated. This comprehensive genetic information provides a foundational genetic resource for strain engineering to enhance secondary metabolite production in Streptomyces.

Published
2022

27. A Tip Mount for Transporting Sensors and Tools using Soft Growing Robots

Author

Jeong, Sang-Goo, Coad, Margaret M., Blumenschein, Laura H., Luo, Ming, Mehmood, Usman, Kim, Ji Hun, Okamura, Allison M., and Ryu, Jee-Hwan

Subjects
Computer Science - Robotics
Abstract

Pneumatically operated soft growing robots that extend via tip eversion are well-suited for navigation in confined spaces. Adding the ability to interact with the environment using sensors and tools attached to the robot tip would greatly enhance the usefulness of these robots for exploration in the field. However, because the material at the tip of the robot body continually changes as the robot grows and retracts, it is challenging to keep sensors and tools attached to the robot tip during actuation and environment interaction. In this paper, we analyze previous designs for mounting to the tip of soft growing robots, and we present a novel device that successfully remains attached to the robot tip while providing a mounting point for sensors and tools. Our tip mount incorporates and builds on our previous work on a device to retract the robot without undesired buckling of its body. Using our tip mount, we demonstrate two new soft growing robot capabilities: (1) pulling on the environment while retracting, and (2) retrieving and delivering objects. Finally, we discuss the limitations of our design and opportunities for improvement in future soft growing robot tip mounts., Comment: Video available at https://youtu.be/eBKRbu_LSYA

Published
2019

29. Adaptive Learning Material Recommendation in Online Language Education

Author

Wang, Shuhan, Wu, Hao, Kim, Ji Hun, and Andersen, Erik

Subjects
Computer Science - Information Retrieval, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

Recommending personalized learning materials for online language learning is challenging because we typically lack data about the student's ability and the relative difficulty of learning materials. This makes it hard to recommend appropriate content that matches the student's prior knowledge. In this paper, we propose a refined hierarchical knowledge structure to model vocabulary knowledge, which enables us to automatically organize the authentic and up-to-date learning materials collected from the internet. Based on this knowledge structure, we then introduce a hybrid approach to recommend learning materials that adapts to a student's language level. We evaluate our work with an online Japanese learning tool and the results suggest adding adaptivity into material recommendation significantly increases student engagement., Comment: The short version of this paper is published at AIED 2019

Published
2019

33. Touching Minds: Deep Generative Models Composing the Digital Contents to Practice Mindfulness

Author

Kim, So Hyeon, Kim, Ji Hun, Yang, Jung Ahn, Lee, Jung Yeon, Lee, Jee Hang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kim, Jong-Hoon, editor, Singh, Madhusudan, editor, Khan, Javed, editor, Tiwary, Uma Shanker, editor, Sur, Marigankar, editor, and Singh, Dhananjay, editor

Published
2022
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43. Markov chain Hebbian learning algorithm with ternary synaptic units

Author

Kim, Guhyun, Kornijcuk, Vladimir, Kim, Dohun, Kim, Inho, Kim, Jaewook, Woo, Hyo Cheon, Kim, Ji Hun, Hwang, Cheol Seong, and Jeong, Doo Seok

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Learning
Abstract

In spite of remarkable progress in machine learning techniques, the state-of-the-art machine learning algorithms often keep machines from real-time learning (online learning) due in part to computational complexity in parameter optimization. As an alternative, a learning algorithm to train a memory in real time is proposed, which is named as the Markov chain Hebbian learning algorithm. The algorithm pursues efficient memory use during training in that (i) the weight matrix has ternary elements (-1, 0, 1) and (ii) each update follows a Markov chain--the upcoming update does not need past weight memory. The algorithm was verified by two proof-of-concept tasks (handwritten digit recognition and multiplication table memorization) in which numbers were taken as symbols. Particularly, the latter bases multiplication arithmetic on memory, which may be analogous to humans' mental arithmetic. The memory-based multiplication arithmetic feasibly offers the basis of factorization, supporting novel insight into the arithmetic., Comment: 25 pages, 4 figures

Published
2017

44. Simulation and Analysis of RF Attacks on Wireless SCADA System

Author

Lee, Sung-Won, Kim, Ji-Hun, Youn, Jonghee, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Park, James J., editor, Fong, Simon James, editor, Pan, Yi, editor, and Sung, Yunsick, editor

Published
2021
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45. Peptide-Programmable Nanoparticle Superstructures with Tailored Electrocatalytic Activity

Author

Kang, Eun Sung, Kim, Yong-Tae, Ko, Young-Seon, Kim, Nam Hyeong, Cho, Geonhee, Huh, Yang Hoon, Kim, Ji-Hun, Nam, Jiyoung, Thach, Trung Thanh, Youn, David, Kim, Young Dok, Yun, Wan Soo, DeGrado, William F, Kim, Sung Yeol, Hammond, Paula T, Lee, Jaeyoung, Kwon, Young-Uk, Ha, Don-Hyung, and Kim, Yong Ho

Subjects
Nanotechnology, Bioengineering, Amino Acid Sequence, Catalysis, Electricity, Gold, Models, Molecular, Nanoparticles, Nanotubes, Carbon, Oxidation-Reduction, Oxygen, Peptides, Platinum, supramolecular protein self-assembly, artificialy designed peptide, nanoparticle superstructure, electron tomography, peptide-based superstructure 3-D reconstruction, peptide-based catalyst, electrocatalytic oxygen reduction, Nanoscience & Nanotechnology
Abstract

Biomaterials derived via programmable supramolecular protein assembly provide a viable means of constructing precisely defined structures. Here, we present programmed superstructures of AuPt nanoparticles (NPs) on carbon nanotubes (CNTs) that exhibit distinct electrocatalytic activities with respect to the nanoparticle positions via rationally modulated peptide-mediated assembly. De novo designed peptides assemble into six-helix bundles along the CNT axis to form a suprahelical structure. Surface cysteine residues of the peptides create AuPt-specific nucleation site, which allow for precise positioning of NPs onto helical geometries, as confirmed by 3-D reconstruction using electron tomography. The electrocatalytic model system, i.e., AuPt for oxygen reduction, yields electrochemical response signals that reflect the controlled arrangement of NPs in the intended assemblies. Our design approach can be expanded to versatile fields to build sophisticated functional assemblies.

Published
2018

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