Article
Multidisciplinary Sciences
Julia Koehler Leman, Sergey Lyskov, Steven M. Lewis, Jared Adolf-Bryfogle, Rebecca F. Alford, Kyle Barlow, Ziv Ben-Aharon, Daniel Farrell, Jason Fell, William A. Hansen, Ameya Harmalkar, Jeliazko Jeliazkov, Georg Kuenze, Justyna D. Krys, Ajasja Ljubetic, Amanda L. Loshbaugh, Jack Maguire, Rocco Moretti, Vikram Khipple Mulligan, Morgan L. Nance, Phuong T. Nguyen, Shane O. Conchuir, Shourya S. Roy Burman, Rituparna Samanta, Shannon T. Smith, Frank Teets, Johanna K. S. Tiemann, Andrew Watkins, Hope Woods, Brahm J. Yachnin, Christopher D. Bahl, Chris Bailey-Kellogg, David Baker, Rhiju Das, Frank DiMaio, Sagar D. Khare, Tanja Kortemme, Jason W. Labonte, Kresten Lindorff-Larsen, Jens Meiler, William Schief, Ora Schueler-Furman, Justin B. Siegel, Amelie Stein, Vladimir Yarov-Yarovoy, Brian Kuhlman, Andrew Leaver-Fay, Dominik Gront, Jeffrey J. Gray, Richard Bonneau
Summary: Vast international resources are wasted on irreproducible research each year, but reproducible scientific software applications can be created by meeting simple design goals. This reproducible design framework is valuable for developers and users of any scientific software, helping the scientific community create reproducible methods.
NATURE COMMUNICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Jade Yu Cheng, Aaron J. Stern, Fernando Racimo, Rasmus Nielsen
Summary: This article presents a new maximum likelihood method for detecting positive selection in the genome, which is orders of magnitude faster than existing techniques. By analyzing simulated and human genomic data, genes related to hair pigmentation, morphology, skin, and eye pigmentation were identified, as well as new candidate regions involving diverse biological functions.
MOLECULAR BIOLOGY AND EVOLUTION
(2022)
Article
Environmental Sciences
Philip E. Dennison, Brian T. Lamb, Michael J. Campbell, Raymond F. Kokaly, W. Dean Hively, Eric Vermote, Phil Dabney, Guy Serbin, Miguel Quemada, Craig S. T. Daughtry, Jeffery Masek, Zhuoting Wu
Summary: Non-photosynthetic vegetation (NPV) is important for terrestrial ecosystem processes and can be used as an indicator for various environmental factors. Current satellite systems have limited capabilities for characterizing NPV cover, but a Continuum Interpolated NPV Depth Index (CINDI) was found to produce low error in estimating NPV cover. CINDI bands showed better performance in dealing with variability and water content. Three SWIR2 bands with specific wavelengths can provide better capabilities for future NPV monitoring. This research has important implications for various applications including soil management, land degradation prevention, drought impacts evaluation, ecosystem disturbance mapping, and wildfire danger assessment.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Biochemical Research Methods
Yunda Si, Chengfei Yan
Summary: AlphaFold2 is able to predict protein complex structures using multiple sequence alignments of interologs. A simplified phylogeny-based approach was applied to generate the alignments, resulting in successful predictions for a high percentage of bacterial and eukaryotic protein-protein interactions. Restricting the interologs to specific taxonomic ranks further improved the success rates.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Environmental Sciences
Meihui Jiang, Haizhong An, Xiangyun Gao
Summary: This study proposes a network-based optimization model that considers the comprehensive influence of the supply chain structure on carbon emissions and compares it with previous non-network models. The results show that the network model can better reduce carbon emissions in different scenarios, and it explores the key industries in the optimization of global industrial structure and the relationship between carbon emission change rate and GDP growth.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Computer Science, Artificial Intelligence
Xiaomin Fang, Fan Wang, Lihang Liu, Jingzhou He, Dayong Lin, Yingfei Xiang, Kunrui Zhu, Xiaonan Zhang, Hua Wu, Hui Li, Le Song
Summary: This study proposes a fast protein structure prediction method by combining a protein language model and AlphaFold2. By utilizing primary structures instead of multiple sequence alignments, the method achieves competitive accuracy and efficiency in structure prediction.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Green & Sustainable Science & Technology
Yuan Xiao, Guomin Cui, Guanhua Zhang, Lianzhong Ai
Summary: This paper investigates the effects of accepting imperfect solutions on the global optimization of heat exchanger network synthesis. A novel parallel optimization route is proposed to balance global and local search ability, and enhancing strategies are integrated to improve the efficiency of structure evolution and global optimization. The effectiveness of the proposed method is verified through case studies.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Electrical & Electronic
Zhonghua Hong, Changyou Xu, Xiaohua Tong, Shijie Liu, Ruyan Zhou, Haiyan Pan, Yun Zhang, Yanling Han, Jing Wang, Shuhu Yang
Summary: This paper proposes a method that can optimize the luminance, contrast, and color difference of remote-sensing images. By processing the chrominance and luminance channels of the image in the YCbCr color space, it reduces the influence of different channels. The proposed method has been tested on challenging datasets and shows better results than state-of-the-art approaches in terms of visuals and quality indicators.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Multidisciplinary Sciences
Dongmin Bang, Sangsoo Lim, Sangseon Lee, Sun Kim
Summary: Computational drug repurposing uses high-throughput data and biomedical knowledge graphs to find new indications for existing drugs. However, learning on these graphs can be challenging due to a limited number of drug and disease entities. To address this, a semantic guilt-by-association approach is proposed, allowing for effective mapping of drugs and diseases. Compared to existing models, the proposed approach improves drug-disease association prediction accuracy and reveals a harmonious relationship between biological and semantic contexts.
NATURE COMMUNICATIONS
(2023)
Article
Automation & Control Systems
Wu Deng, Junjie Xu, Xiao-Zhi Gao, Huimin Zhao
Summary: In this paper, an enhanced MSIQDE algorithm based on mixing multiple strategies, called EMMSIQDE, is proposed to overcome the limitations of QDE in optimization problems. EMMSIQDE achieves better optimization performance by using new mutation strategies and evolution mechanisms, as well as a feasible solution space transformation strategy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Computer Science, Information Systems
Zhu Wang, Jiaxun Liu, Dong Wang, Wei Wang
Summary: This paper investigates the distributed cooperative optimization problem with globally equality and inequality constraints for a multi-agent system, proposes two continuous-time algorithms, and proves that the algorithms converge to the optimal solution when the parameters of EL agents are known, and converge asymptotically to the optimal solution when the parameters of EL agents are unknown.
INFORMATION SCIENCES
(2021)
Article
Chemistry, Physical
Luping Han, Gui-Duo Jiang, Xiao-Na Li, Sheng-Gui He
Summary: In this study, global optimization was conducted on Ta-n (n = 9-13) clusters using a combination of deep neural network (DNN) and density functional theory (DFT) method. The calculations confirmed all previously known cluster isomers within a relative energy of 1.5 eV, except for Ta-10 which had a threshold of 2.0 eV, and reported new isomers within the same relative energy range. The DNN method was found to better explore more complex high-dimensional PESs for larger-sized clusters, leading to the discovery of new low-lying energy isomer configurations.
CHEMICAL PHYSICS LETTERS
(2021)
Article
Microbiology
Pascal Mutz, Wolfgang Resch, Guilhem Faure, Tatiana G. Senkevich, Eugene V. Koonin, Bernard Moss
Summary: Protein structures are more conserved in evolution than amino acid sequences, making comparative structural analysis important for tracing the origins of rapidly evolving viral proteins. By using AlphaFold2, the structures of orthopoxvirus proteins were predicted, revealing the exaptation of host enzymes for nonenzymatic roles in virus reproduction. This study highlights the unique structural folds of many viral proteins.
Article
Chemistry, Medicinal
Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu
Summary: Understanding the relationship between composition, structure, and function in materials is crucial for discovering and designing new functional materials. In this study, we globally mapped all known materials in the Materials Project database to investigate their distribution in a set of seven descriptors. These maps provide a comprehensive overview of materials and space, revealing previously undescribed fundamental properties.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Electrochemistry
W. Olbrich, T. Kadyk, U. Sauter, M. Eikerling
Summary: This study presents a structure-based model that predicts wetting phenomena inside the cathode catalyst layer of polymer electrolyte fuel cells, thus achieving optimal water management. Compared to existing modeling approaches, this model provides a more accurate description of wetting behavior and can be used for fuel cell design and optimization.
ELECTROCHIMICA ACTA
(2022)
Article
Nanoscience & Nanotechnology
Seonyeong Kim, Dong Hoon Shin, Yong-Sung Kim, In-Ho Lee, Chang-Won Lee, Sunae Seo, Suyong Jung
Summary: The energy band alignments and material properties at the contacts between metal and 2D semiconducting transition metal dichalcogenide films are essential for electronic and optical device applications. Vertical diodes with asymmetric metal-SCTMD contact areas were used to study contact-limited charge flows in tunneling and emission transport regimes. The experimental and analytical approaches demonstrated in this research provide a powerful tool for evaluating metal-SCTMD contacts qualitatively and quantitatively.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Materials Science, Multidisciplinary
In-Ho Lee, K. J. Chang
Summary: This method uses machine learning to predict new low-energy crystal structures by generating crystal replicas with similar features through radial distribution functions and variational autoencoder. Additionally, energy minimization is performed on selected crystal structures through first-principles electronic structure calculations to obtain the predicted crystal structures.
COMPUTATIONAL MATERIALS SCIENCE
(2021)
Article
Chemistry, Multidisciplinary
Beomchang Kang, Chaok Seok, Juyong Lee
Summary: Fluorescent dyes play crucial roles in chemical and biological imaging, and an accurate computational model for evaluating the electronic properties of molecules is important for discovering novel fluorophores. In this study, a benchmark test was conducted to predict electronic transition properties, and DimeNet++ was identified as the most accurate model, while D-MPNN showed the fastest prediction speed at the expense of some accuracy.
BULLETIN OF THE KOREAN CHEMICAL SOCIETY
(2022)
Article
Biology
Jinyoung Byun, Juyong Lee
Summary: This study investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its ligands to identify the hot spot residues. Molecular dynamics simulations and MM-PBSA analysis were performed with three different force fields to assess their influence on hot spot residue identification and binding free energy calculation. The results showed weak correlations between the MM-PBSA estimations using different force fields, highlighting the dependence of MM-PBSA analysis results on force fields. The study also identified the hot spot residues and their critical interactions with ligands through energy decomposition analysis.
Article
Biochemical Research Methods
Yiyu Hong, Juyong Lee, Junsu Ko
Summary: This study proposes a new protein 3D structure modeling method called A-Prot, using MSA Transformer, one of the state-of-the-art protein language models. The results show that A-Prot accurately predicts long-range contacts and produces more accurate models than most top server groups of CASP14. This indicates that A-Prot effectively captures evolutionary and structural information of proteins with relatively low computational cost.
BMC BIOINFORMATICS
(2022)
Article
Chemistry, Physical
Ada Y. Chen, Juyong Lee, Ana Damjanovic, Bernard R. Brooks
Summary: Protonation states of ionizable protein residues are crucial for biological processes, and accurately determining their pKa values is essential. This study introduces four tree-based machine learning models for protein pKa prediction, achieving improved performance on a large dataset.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Biochemistry & Molecular Biology
Cheol-Hee Shin, Su Chan Park, Il-Geun Park, Hyerim Kim, Byoungha An, Choongil Lee, Sang-Heon Kim, Juyong Lee, Ji Min Lee, Seung Ja Oh
Summary: Researchers have developed a platform called mRNA bridge mimetics that mimics the microRNA-mediated mRNA decay mechanism to regulate protein translocation. They successfully demonstrated programmed gene editing in vitro and in vivo using this platform and also improved sensitivity to chemotherapeutic drugs through a combination of chemotherapy and gene modification techniques. This strategy has the potential to play a role in disease treatment.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Multidisciplinary Sciences
Umit Ucak, Islambek Ashyrmamatov, Junsu Ko, Juyong Lee
Summary: The study presents a new approach for retrosynthetic prediction using fragments and the Transformer architecture. By learning the changes in atom environments, the method predicts reactant candidates for chemical reactions, achieving high accuracy in reaction route prediction and discovery.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Sung Jong Lee, Keehyoung Joo, Sangjin Sim, Juyong Lee, In-Ho Lee, Jooyoung Lee
Summary: This paper presents a method called CRFalign for sequence-structure alignment of proteins, which achieves good alignment accuracy and template search performance for remote homologue target proteins.
Article
Chemistry, Physical
Keun-Hong Min, Duk Hyun Lee, Sang-Jun Choi, In-Ho Lee, Junho Seo, Dong Wook Kim, Kyung-Tae Ko, Kenji Watanabe, Takashi Taniguchi, Dong Han Ha, Changyoung Kim, Ji Hoon Shim, Jonghwa Eom, Jun Sung Kim, Suyong Jung
Summary: The authors investigate the tunnelling magnetoresistance in Fe3GeTe2/hBN(WSe2)/Fe3GeTe2 magnetic tunnel junctions and report strong variations including polarization reversals with bias. Using van der Waals heterostructures with two-dimensional magnets, they demonstrate electrically tunable spin injection and detection, as well as modulated and reversed net spin polarization of the injected carriers, leading to changes in tunnelling magnetoresistance. The authors attribute the spin polarization reversals to contributions from high-energy localized spin states in the metallic ferromagnet, which is inaccessible in conventional magnetic junctions.
Article
Chemistry, Multidisciplinary
Jinyoung Byun, Srivithya Vellampatti, Prathit Chatterjee, Sun Ha Hwang, Byoung Choul Kim, Juyong Lee
Summary: A significant difference between APP695 and APP751 isoforms is the presence of the Kunitz type protease inhibitor (KPI) domain, which affects the dimerization of APP isoforms. Through experiments and simulations, it was discovered that homo-dimerization is favored for both isoforms, while hetero-dimerization is limited between APP751 and APP695. The KPI domain has a stronger attractive interaction with itself and other domains in APP751, leading to its predominant homo-dimer formation.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2023)
Article
Integrative & Complementary Medicine
Jong-In Park, In-Ho Lee, Seung-Jea Lee, Ryeo-Won Kwon, Eon-Ah Choo, Hyun-Woo Nam, Jeong-Beom Lee
Summary: The study aimed to determine the effect of music therapy as an alternative treatment for depression in children and adolescents with ADHD by activating serotonin (5-HT) and improving stress coping ability. The study used randomization method and included 36 subjects. The results showed that music therapy had positive effects on neurophysiological and psychological measures, such as increased 5-HT secretion and decreased cortisol expression, blood pressure, and heart rate.
BMC COMPLEMENTARY MEDICINE AND THERAPIES
(2023)
Article
Chemistry, Multidisciplinary
Min-Sik Kim, Dong-Hwan Choi, In-Ho Lee, Wu-Sin Kim, Duhyuk Kwon, Myung-Ho Bae, Ju-Jin Kim
Summary: In this study, researchers report reversible electrical phase transitions in Mo0.67W0.33Se2 (MoWSe) materials, which can be tuned by gate voltage. Electrical current resumes flow in the gate-induced depletion region of the 2H phase when the temperature decreases between 150 K and 200 K. Additionally, the formation of conducting channels and negative differential transconductance were observed. Hysteresis measurements confirm the reversibility of the electrical phase transition behavior.
Article
Chemistry, Multidisciplinary
Nicholas Asiimwe, Mohammad Faysal Al Mazid, Yong Taek Jeong, Juyong Lee, Jun-Seok Lee
Summary: In this study, inhibitors for the formylglycine-generating enzyme were investigated and two hit peptides were discovered. Additionally, these lead peptides showed potential antibacterial effects in a Mycobacterium tuberculosis model.
