Article
Acoustics
P. Cheema, M. Makki Alamdari, G. A. Vio, F. L. Zhang, C. W. Kim
Summary: The paper presents a novel approach based on DP-GMM for analyzing the stabilization diagram, achieving fully automated modal identification without the need for manual parameter specification. The method is validated to have superior performance, high computational efficiency, and justified new feature vectors.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Automation & Control Systems
Matthias Eckhart, Andreas Ekelhart, Stefan Biffl, Arndt Lueder, Edgar Weippl
Summary: As cyber threats in industrial domain increase, security-by-design is becoming a crucial concern in the engineering of cyber-physical production systems (CPPSs). This paper highlights the importance of integrating quality considerations into security-aware CPPS engineering to address the attack vectors that could affect product quality. The proposed QualSec method utilizes a semantic representation of engineering knowledge, AutomationML artifacts, and Petri nets to automatically identify security risks, analyze cascading effects, and inform users about possible attack paths and consequences.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Cell Biology
Jordan A. Berg, Youjia Zhou, Yeyun Ouyang, Ahmad A. Cluntun, T. Cameron Waller, Megan E. Conway, Sara M. Nowinski, Tyler Van Ry, Ian George, James E. Cox, Bei Wang, Jared Rutter
Summary: Berg et al. present Metaboverse, a tool that automates the discovery and visualization of metabolic data. It allows users to extract meaningful patterns from multi-omics datasets to describe metabolic responses and signatures. Metabolism plays a crucial role in various cellular processes, and Metaboverse overcomes current limitations in metabolic data interpretation.
NATURE CELL BIOLOGY
(2023)
Article
Environmental Sciences
Yaoxing Wu, Shanique Grant, Wenlin Chen, Arpad Szarka
Summary: This study developed a novel data-driven approach to accurately determine the annual maximum daily concentration (AMDC) of pesticides in surface waters. Using time series modeling and machine learning models, the approach demonstrated significant predictability, with the hybrid model achieving the highest prediction accuracy. Pesticide use and drainage area were identified as the most important drivers.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Editorial Material
Biotechnology & Applied Microbiology
Andrew S. Robertson, Alexis Reisin Miller, Felipe Dolz
Summary: Drug developers are increasingly using data-driven analysis to understand regulatory agencies' expectations, but are limited by the availability and quality of regulatory datasets. Establishing a single, robust FDA regulatory actions database could help address this limitation.
NATURE REVIEWS DRUG DISCOVERY
(2021)
Article
Microbiology
Mario L. Arrieta-Ortiz, Selva Rupa Christinal Immanuel, Serdar Turkarslan, Wei-Ju Wu, Brintha P. Girinathan, Jay N. Worley, Nicholas DiBenedetto, Olga Soutourina, Johann Peltier, Bruno Dupuy, Lynn Bry, Nitin S. Baliga
Summary: By leveraging published transcriptomes and metabolic models, we developed a predictive model for comprehensive systems analysis of Clostridioides difficile, shedding light on gene organization and metabolic requirements, as well as the role of transcription factors in growth and ecological adaptation.
CELL HOST & MICROBE
(2021)
Article
Immunology
Jennifer C. Whitesell, Robin S. Lindsay, Jessica G. Olivas-Corral, Seth F. Yannacone, Mary H. Schoenbach, Erin D. Lucas, Rachel S. Friedman
Summary: The study investigated the phenotype and function of lymphocytes in islets, revealing a regulatory phenotype in islet T cells and B cells under steady-state conditions, potentially playing a protective role in maintaining tissue homeostasis. Effector function analysis showed the production of the regulatory cytokine IL-10 by islet T cells and B cells, which remained stable even under metabolic stress in the diet-induced obesity (DIO) model. T cells in human islets retained a similar activated and memory phenotype in non-diabetic and T2D donors.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Computer Science, Information Systems
Abdelhak Bentaleb, Ali C. Begen, Saad Harous, Roger Zimmermann
Summary: The research proposes an Automated Model for Prediction (AMP) technology to enhance the performance of low-latency live streaming through bandwidth prediction and automated model selection. Various bandwidth prediction models are implemented to work accurately under different network conditions, and an automated model selection method is introduced.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Article
Plant Sciences
Sebastian Huss, Rika Siedah Judd, Kaan Koper, Hiroshi A. Maeda, Zoran Nikoloski
Summary: By establishing an automated workflow, reliable atom mappings for large-scale metabolic models can be obtained. This method can be applied to metabolic models of different species and facilitates metabolic flux analysis and structural analysis.
Article
Computer Science, Artificial Intelligence
Kebin Sun, Weituo Wang, Ran Cheng, Yu Liang, Hairun Xie, Jing Wang, Miao Zhang
Summary: This paper introduces a highly automated approach for supercritical airfoil design, called Evolutionary Generative Design (EvoGD), which improves aerodynamic performance and reduces constraint violations. It utilizes sophisticated data-driven generative models and accurate predictors to iteratively refine initial airfoil shapes. Experimental results show that the generated airfoils have improved performance in terms of buffet lift coefficient, cruise lift-to-drag ratio, and thickness. The entire design process can be completed in less than an hour on a personal computer, highlighting the high efficiency and scalability of the EvoGD approach.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Biochemical Research Methods
Woosub Shin, John H. Gennari, Joseph L. Hellerstein, Herbert M. Sauro
Summary: Motivation annotations play a crucial role in providing detailed information regarding biochemical models. However, existing models often lack sufficient annotations, making it challenging to understand their limitations. To address this issue, the researchers developed AMAS, a system that predicts annotations for elements in biochemical models. AMAS employs a general framework that utilizes a database of annotated reference elements and a match score function to calculate the similarity between query and reference elements. The system demonstrates high computational efficiency and prediction accuracy, with response times in the subsecond range and accuracy rates between 80% and 95%, depending on the specific predictions. AMAS has been integrated into an open-source Python package and can be utilized as a command-line tool to predict and add annotations to species and reactions in SBML models.
Article
Computer Science, Information Systems
Md. Jueal Mia, Rafat Bin Mahmud, Md. Safein Sadad, Hafiz Al Asad, Rafat Hossain
Summary: Fish plays a crucial role in food and nutritional security, but its production is declining due to diseases. This article aims to effectively identify fish diseases through image recognition technology, providing necessary support to farmers. Experimental results show that using smartphones and expert systems for disease identification is efficient and accurate.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Materials Science, Characterization & Testing
Xiuyuan Yang, Wenjuan Sun, Claudiu L. Giusca
Summary: This paper investigates the critical step of surface determination in X-ray Computed Tomography, demonstrating the effectiveness of the marker-controlled watershed algorithm in automating the process and improving its performance.
NDT & E INTERNATIONAL
(2022)
Article
Multidisciplinary Sciences
Philip Fernandes, Yash Sharma, Fatima Zulqarnain, Brooklyn McGrew, Aman Shrivastava, Lubaina Ehsan, Dawson Payne, Lillian Dillard, Deborah Powers, Isabelle Aldridge, Jason Matthews, Subra Kugathasan, Facundo M. Fernandez, David Gaul, Jason A. Papin, Sana Syed
Summary: Crohn's disease is a chronic inflammatory disease of the gastrointestinal tract. The lack of highly specific biomarkers for disease management is a problem in current diagnostics and treatment approaches. This study presents a framework that utilizes machine learning and metabolic modeling to study altered metabolic reactions in patients with Crohn's disease, aiming to discover novel diagnostic biomarkers and therapeutic targets.
SCIENTIFIC REPORTS
(2023)
Article
Green & Sustainable Science & Technology
Haoteng Zhao, Liping Di, Liying Guo, Chen Zhang, Li Lin
Summary: Given the increasing prevalence of droughts, unpredictable rainfall patterns, and limited access to dependable water sources, it has become crucial to implement effective irrigation scheduling strategies. This study developed and evaluated an automated data-driven irrigation scheduling approach by integrating High-Resolution Land Data Assimilation System (HRLDAS) products and the crop growth model (AquaCrop). The results showed significant water-saving potential without compromising crop yield.
Article
Biotechnology & Applied Microbiology
Morgann C. Reilly, Joonhoon Kim, Jed Lynn, Blake A. Simmons, John M. Gladden, Jon K. Magnuson, Scott E. Baker
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
(2018)
Article
Biotechnology & Applied Microbiology
Kyle R. Pomraning, James R. Collett, Joonhoon Kim, Ellen A. Panisko, David E. Culley, Ziyu Dai, Shuang Deng, Beth A. Hofstad, Mark G. Butcher, Jon K. Magnuson
BIOTECHNOLOGY FOR BIOFUELS
(2019)
Article
Biotechnology & Applied Microbiology
Luisa Czamanski Nora, Maren Wehrs, Joonhoon Kim, Jan-Fang Cheng, Angela Tarver, Blake A. Simmons, Jon Magnuson, Miranda Harmon-Smith, Rafael Silva-Rocha, John M. Gladden, Aindrila Mukhopadhyay, Jeffrey M. Skerker, James Kirby
MICROBIAL CELL FACTORIES
(2019)
Article
Biochemical Research Methods
Joonhoon Kim, Mary Tremaine, Jeffrey A. Grass, Hugh M. Purdy, Robert Landick, Patricia J. Kiley, Jennifer L. Reed
BIOTECHNOLOGY JOURNAL
(2019)
Review
Biotechnology & Applied Microbiology
Christopher E. Lawson, Jose Manuel Marti, Tijana Radivojevic, Sai Vamshi R. Jonnalagadda, Reinhard Gentz, Nathan J. Hillson, Sean Peisert, Joonhoon Kim, Blake A. Simmons, Christopher J. Petzold, Steven W. Singer, Aindrila Mukhopadhyay, Deepti Tanjore, Joshua G. Dunn, Hector Garcia Martin
Summary: The review introduces how machine learning can make metabolic engineering more predictable, provides examples and advice, discusses various applications, and examines future prospects.
METABOLIC ENGINEERING
(2021)
Article
Biotechnology & Applied Microbiology
Yuqian Gao, Thomas L. Fillmore, Nathalie Munoz, Gayle J. Bentley, Christopher W. Johnson, Joonhoon Kim, Jamie A. Meadows, Jeremy D. Zucker, Meagan C. Burnet, Anna K. Lipton, Aivett Bilbao, Daniel J. Orton, Young-Mo Kim, Ronald J. Moore, Errol W. Robinson, Scott E. Baker, Bobbie-Jo M. Webb-Robertson, Adam M. Guss, John M. Gladden, Gregg T. Beckham, Jon K. Magnuson, Kristin E. Burnum-Johnson
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2020)
Article
Biotechnology & Applied Microbiology
Joonhoon Kim, Samuel T. Coradetti, Young-Mo Kim, Yuqian Gao, Junko Yaegashi, Jeremy D. Zucker, Nathalie Munoz, Erika M. Zink, Kristin E. Burnum-Johnson, Scott E. Baker, Blake A. Simmons, Jeffrey M. Skerker, John M. Gladden, Jon K. Magnuson
Summary: This study conducted multi-omics analysis on the utilization of lignocellulosic carbon in the oleaginous yeast Rhodosporidium toruloides, resulting in the successful reconstruction of its genome-scale metabolic network. The developed metabolic model was validated, refined, and believed to be the most complete and accurate model for R. toruloides to date.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Biotechnology & Applied Microbiology
Somtirtha Roy, Tijana Radivojevic, Mark Forrer, Jose Manuel Marti, Vamshi Jonnalagadda, Tyler Backman, William Morrell, Hector Plahar, Joonhoon Kim, Nathan Hillson, Hector Garcia Martin
Summary: Biology has evolved from a descriptive science to a design science, utilizing computational tools to predict bioengineering outcomes by integrating multiomics data. By uploading, visualizing, and outputting data to online repositories, and training machine learning algorithms to recommend new strain designs, improvements in production can be achieved in bioengineered strains.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Biotechnology & Applied Microbiology
James Kirby, Gina M. Geiselman, Junko Yaegashi, Joonhoon Kim, Xun Zhuang, Mary Bao Tran-Gyamfi, Jan-Philip Prahl, Eric R. Sundstrom, Yuqian Gao, Nathalie Munoz, Kristin E. Burnum-Johnson, Veronica T. Benites, Edward E. K. Baidoo, Anna Fuhrmann, Katharina Seibel, Bobbie-Jo M. Webb-Robertson, Jeremy Zucker, Carrie D. Nicora, Deepti Tanjore, Jon K. Magnuson, Jeffrey M. Skerker, John M. Gladden
Summary: This study optimized the production of monoterpene 1,8-cineole and sesquiterpene alpha-bisabolene in R. toruloides. Increasing the copy number of bisabolene synthase (BIS) and enhancing the expression of GPP synthase improved the production of alpha-bisabolene and 1,8-cineole, respectively, from lignocellulosic hydrolysate. Targeted overexpression of mevalonate pathway genes further increased the terpene production, bringing R. toruloides closer to industrial relevance.
BIOTECHNOLOGY FOR BIOFUELS
(2021)
Article
Biochemical Research Methods
Ziyu Dai, Kyle R. Pomraning, Ellen A. Panisko, Beth A. Hofstad, Kristen B. Campbell, Joonhoon Kim, Ana L. Robles, Shuang Deng, Jon K. Magnuson
Summary: The research demonstrates the production of high levels of alpha-zingiberene in oleaginous yeast through transgenic methods, with further improvements possible through optimization of growth media. This study opens up a new synthetic route for the production of alpha-zingiberene in Lipomyces starkeyi and establishes this yeast as a platform for jet fuel biosynthesis.
ACS SYNTHETIC BIOLOGY
(2021)
Article
Biotechnology & Applied Microbiology
Kyle R. Pomraning, Ziyu Dai, Nathalie Munoz, Young-Mo Kim, Yuqian Gao, Shuang Deng, Joonhoon Kim, Beth A. Hofstad, Marie S. Swita, Teresa Lemmon, James R. Collett, Ellen A. Panisko, Bobbie-Jo M. Webb-Robertson, Jeremy D. Zucker, Carrie D. Nicora, Henrique De Paoli, Scott E. Baker, Kristin E. Burnum-Johnson, Nathan J. Hillson, Jon K. Magnuson
Summary: Integrated multi-omic analyses were used to identify metabolic pathways and factors limiting the overproduction of 3-hydroxypropionic acid in the filamentous fungus Aspergillus pseudoterreus, leading to a significant improvement in yield and potential for industrial scale biomanufacturing of organic acids.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Biotechnology & Applied Microbiology
Kyle R. Pomraning, Ziyu Dai, Nathalie Munoz, Young-Mo Kim, Yuqian Gao, Shuang Deng, Teresa Lemmon, Marie S. Swita, Jeremy D. Zucker, Joonhoon Kim, Stephen J. Mondo, Ellen Panisko, Meagan C. Burnet, Bobbie-Jo M. Webb-Robertson, Beth Hofstad, Scott E. Baker, Kristin E. Burnum-Johnson, Jon K. Magnuson
Summary: The global regulator LaeA plays a crucial role in controlling secondary metabolism in diverse Aspergillus species. This study reveals its importance in regulating itaconic acid production in Aspergillus pseudoterreus. Overexpression of LaeA enhances itaconic acid yield by increasing the expression of key biosynthetic pathway enzymes and attenuating the expression of genes involved in phosphate acquisition and scavenging.
METABOLIC ENGINEERING COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Aivett Bilbao, Nathalie Munoz, Joonhoon Kim, Daniel J. Orton, Yuqian Gao, Kunal Poorey, Kyle R. Pomraning, Karl Weitz, Meagan Burnet, Carrie D. Nicora, Rosemarie Wilton, Shuang Deng, Ziyu Dai, Ethan Oksen, Aaron Gee, Rick A. Fasani, Anya Tsalenko, Deepti Tanjore, James Gardner, Richard D. Smith, Joshua K. Michener, John M. Gladden, Erin S. Baker, Christopher J. Petzold, Young-Mo Kim, Alex Apffel, Jon K. Magnuson, Kristin E. Burnum-Johnson
Summary: Alternative algorithms leveraging the advantages of multidimensional mass spectrometry are necessary for untargeted metabolomics research. The authors have developed and demonstrated PeakDecoder, which enables confident and accurate metabolite profiling. This algorithm was applied to analyze 116 microbial sample runs using a library of 64 standards.
NATURE COMMUNICATIONS
(2023)
Article
Biotechnology & Applied Microbiology
Ziyu Dai, Kyle R. R. Pomraning, Shuang Deng, Joonhoon Kim, Kristen B. B. Campbell, Ana L. L. Robles, Beth A. A. Hofstad, Nathalie Munoz, Yuqian Gao, Teresa Lemmon, Marie S. S. Swita, Jeremy D. D. Zucker, Young-Mo Kim, Kristin E. E. Burnum-Johnson, Jon K. K. Magnuson
Summary: This study introduced the biosynthesis pathway of 3-hydroxypropionic acid (3-HP) into Aspergillus niger and improved its production yield through metabolic engineering. The results confirmed that A. niger is a suitable host for 3-HP production from lignocellulosic feedstock. By identifying and modifying genes related to the synthesis of 3-HP and its precursors, degradation of intermediates, and transport across the plasma membrane, the researchers were able to significantly improve the yield.
BIOTECHNOLOGY FOR BIOFUELS AND BIOPRODUCTS
(2023)
Review
Biochemical Research Methods
Yichao Han, Albert Tafur Rangel, Kyle R. Pomraning, Eduard J. Kerkhoven, Joonhoon Kim
Summary: Genome-scale metabolic models (GEMs) provide a comprehensive view of fungal cellular metabolism and enhance performance predictions in biomanufacturing.
CURRENT OPINION IN BIOTECHNOLOGY
(2023)