Article
Computer Science, Artificial Intelligence
Yen-Hsien Lee, Paul Jen-Hwa Hu, Wan-Jung Tsao, Liang Li
Summary: The increasing volume of textual documents created by modern information technology has made automated document organization crucial. This study proposes a concept-based text categorization method that incorporates a domain-specific ontology for more effective document categorization. Empirical evaluations show that the proposed method outperforms benchmark techniques, demonstrating high computational efficiency and clear classification patterns.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Irina Leshcheva, Alena Begler
Summary: This article proposes an ontology-based method for knowledge base creation, which allows for the simultaneous integration of different data sources in various formats and provides extensibility. The method involves data specification and data-to-ontology schema mapping to insert data into the domain ontology.
JOURNAL OF INFORMATION SCIENCE
(2022)
Article
Computer Science, Information Systems
Zhiyu Pan, Yuting Gao, Ferdinanda Ponci, Antonello Monti
Summary: This paper presents a semi-automatic ontology development framework for managing heterogeneous data in the building sector, specifically focusing on building energy management. The framework integrates existing automatic ontology tools and reuses existing ontology and data models.
Article
Environmental Sciences
Heather Schovanec, Gabriel Walton, Ryan Kromer, Adam Malsam
Summary: This study introduces a workflow for automating the generation of rockfall databases using terrestrial laser scanning, highlighting the importance of adapting commonly used algorithms for rockfall monitoring use cases.
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
Biochemical Research Methods
Andrew Sayad, Yusuf Oduntan, Norbert Bokros, Seth DeBolt, Alice Benzecry, Daniel J. J. Robertson, Christopher J. J. Stubbs
Summary: This study presents a methodology for the high-throughput digitization and quantification of plant cell walls characterization, using automated development of two-dimensional finite element models and custom algorithms based on machine learning. Compound microscope images of herbaceous and woody representatives were used to demonstrate the utility of these models, and parametric analyses were performed on the resulting finite element models. Sensitivity analyses showed that the cell wall thickness has a three-fold larger impact on tissue stiffness than the cell wall elastic modulus.
Article
Engineering, Multidisciplinary
Weidong Lei, Hai Zhou, Hongjun Li, Rui Chen
Summary: This paper develops a time domain boundary element method for analyzing the dynamic response of twin-parallel circular tunnels in an elastic semi-infinite medium. The method involves constructing virtual boundaries to reference the boundary integral equations for a single circular tunnel, and provides detailed numerical treatment for validation of applicability and efficiency.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2021)
Article
Education & Educational Research
Guozhu Ding, Xiangyi Shi, Shan Li
Summary: In this study, a classification system of programming errors was developed based on the historical data of over 680,540 programming records collected on an Online Judge platform. The system described six types of programming errors and their connections with fundamental programming knowledge. Furthermore, student and problem ontologies were created using ontology-based learner modeling techniques, providing accurate representations of student information and problem characteristics. An automated system for assigning programming tasks to students was designed based on the classification system and knowledge graphs. The effectiveness of the automated task assignment system was tested using a quasi-experimental design, showing no significant difference in student performance compared to traditional assignment methods.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Software Engineering
Minjeong Shin, Joohee Kim, Yunha Han, Lexing Xie, Mitchell Whitelaw, Bum Chul Kwon, Sungahn Ko, Niklas Elmqvist
Summary: Roslingifier is a data-driven storytelling method that transforms a sequence of changing entities (such as countries and continents with demographic data) into engaging narratives, using techniques like natural language narratives, visual effects, and temporal branching.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2023)
Article
Chemistry, Analytical
Christopher Mc Eleney, Martin Bradley, Sheila Alves, Denis Mc Crudden
Summary: This study introduces a low-cost method for monitoring the level of nutrients in soil and their availability for crops.
ANALYTICAL METHODS
(2022)
Article
Chemistry, Multidisciplinary
Roua Jabla, Maha Khemaja, Felix Buendia, Sami Faiz
Summary: Knowledge engineering relies on ontologies for formal descriptions of real-world knowledge, and ontology learning is seen as a helpful approach to generating ontologies semi-automatically or automatically. This approach not only improves efficiency in ontology development, but also extends preexisting ontologies with new knowledge from diverse input data forms. The presented automatic ontology-based model evolution approach aims to cope with dynamic environments by analyzing semi-structured input data for learning and extending ontologies at runtime.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Lawrence Bunnell, Kweku-Muata Osei-Bryson, Victoria Y. Yoon
Summary: This research presents a consumer financial goals ontology designed for use as a knowledgebase in recommender systems applications to support decision-making in financial planning. It addresses the lack of a formal conceptual model or knowledge classification of financial goals within the consumer financial planning domain. The ontology contributes to the research knowledgebase by providing a framework for indexing and retrieval within applications aimed at improving consumer financial capability through identification and recommendation of specific financial goals.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Medicine, Research & Experimental
Korawich Uthayopas, Alex G. C. de Sa, Azadeh Alavi, Douglas E. Pires, David B. Ascher
Summary: The emergence of high-throughput sequencing techniques has highlighted the importance of miRNAs in diseases, with the TSMDA machine-learning method showing superiority in predicting miRNA-disease associations. This method has the potential to uncover new associations and aid in further experimental characterization.
MOLECULAR THERAPY-NUCLEIC ACIDS
(2021)
Article
Chemistry, Physical
Bartlomiej Sawicki, Tomasz Piotrowski, Andrzej Garbacz
Summary: The UIR-Scanner, developed at Warsaw University of Technology, combines multiple nondestructive testing methods to speed up the assessment of concrete and increase precision. The Impact-Echo module with a unique arrangement of multiple transducers allows for quick scanning of area for faults and discontinuities, changing the method from punctual to volumetric.
Article
Computer Science, Artificial Intelligence
Jichang Li, Guanbin Li, Yizhou Yu
Summary: Semi-supervised domain adaptation aims to improve classification performance by leveraging labeled data from the target domain. However, due to the scarcity of label information, previous methods were not able to fully realize their potential. In this study, a graph-based adaptive betweenness clustering approach is proposed to achieve categorical domain alignment and propagate semantic labels to unlabeled target data.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2023)
Article
Biochemistry & Molecular Biology
Martin Ringwald, Joel E. Richardson, Richard M. Baldarelli, Judith A. Blake, James A. Kadin, Cynthia Smith, Carol J. Bult
Summary: The Mouse Genome Informatics (MGI) database system combines expertly curated community data resources to facilitate the use of the mouse as an experimental model for understanding human health and disease genetics. MGI is the authoritative source for mouse gene information, maintains standard ontologies, and contributes to the development of gene and disease ontologies.
Article
Substance Abuse
Nurul Atiqahd Muhamad Fauzi, Mei Lan Tan, Shahrul Bariyah Sahul Hamid, Darshan Singh, Mohammad Farris Iman Leong Bin Abdullah
Summary: This study found an association between the expression of ER stress sensor mRNA in peripheral leukocytes and patterns of kratom use. It also identified correlations between the levels of ER stress sensor mRNA and the severity of kratom dependence and kratom induced depressive symptoms.
JOURNAL OF ADDICTION MEDICINE
(2022)
Article
Cell Biology
Alexander B. Coley, Ashlyn N. Stahly, Mohan Kasukurthi, Addison A. Barchie, Sam B. Hutcheson, Dominika Houserova, Yulong Huang, Brianna C. Watters, Valeria M. King, Meghan A. Dean, Justin T. Roberts, Jeffrey D. DeMeis, Krisha Amin, Cameron H. McInnis, Noel L. Godang, Ryan M. Wright, David F. Haider, Neha B. Piracha, Cana L. Brown, Zohaib M. Ijaz, Shengyu Li, Yaguang Xi, Oliver G. McDonald, Jingshan Huang, Glen M. Borchert
Summary: This study identified differentially expressed snoRNA fragments in prostate cancer patients and found that two specific fragments, sdRNA-D19b and -A24, play important roles in promoting proliferation, migration, and chemotherapeutic resistance in prostate cancer. The targets of sdRNA-D19b and sdRNA-A24 were identified as tumor suppressor genes CD44 and CDK12, respectively.
Article
Cell Biology
Mingwei Liang, Jennifer W. Li, Huacheng Luo, Sarah Lulu, Ozlem Calbay, Anitha Shenoy, Ming Tan, Brian K. Law, Shuang Huang, Tsan Sam Xiao, Hao Chen, Lizi Wu, Jia Chang, Jianrong Lu
Summary: This study found that EMT suppresses the expression of AMPK genes and affects AMPK activation, leading to increased sensitivity of cancer cells to pyroptotic cell death under energy stress conditions. AMPK expression in tumors is associated with clinical prognosis. EMT-induced collateral vulnerabilities may be therapeutically exploited.
Review
Biochemistry & Molecular Biology
Alexander Bishop Coley, Jeffrey David DeMeis, Neil Yash Chaudhary, Glen Mark Borchert
Summary: In the past decade, sdRNAs derived from snoRNAs have emerged as important regulators in cancer gene expression. They possess miRNA-like functions and can act as oncogenic or tumor-suppressing RNAs depending on the tissue context. Despite being frequently overlooked in non-coding RNA analyses, sdRNAs represent a subclass of miRNAs that deserve further study to uncover their underlying biology and identify potential biomarkers and therapeutic targets for various human cancers.
Article
Multidisciplinary Sciences
Anusha Angajala, Hughley Raymond, Aliyu Muhammad, Md Shakir Uddin Ahmed, Saadia Haleema, Monira Haque, Honghe Wang, Moray Campbell, Rachel Martini, Balasubramanian Karanam, Andrea G. Kahn, Deepa Bedi, Melissa Davis, Ming Tan, Windy Dean-Colomb, Clayton Yates
Summary: The study revealed that QNBC tumors are more common in African Americans compared to TNBC tumors. By analyzing miRNA and mRNA expression data, it was found that QNBC patients have an altered gene signature associated with racial disparity and poor survival.
SCIENTIFIC REPORTS
(2022)
Article
Cell Biology
Ritu Arora, Jin-Hwan Kim, Ayechew A. Getu, Anusha Angajala, Yih-Lin Chen, Bin Wang, Andrea G. Kahn, Hong Chen, Latif Reshi, Jianrong Lu, Wenling Zhang, Ming Zhou, Ming Tan
Summary: The highly expressed MST4 gene in breast cancer promotes cell growth, migration, invasion, and epithelial-mesenchymal transition (EMT). It is associated with cancer stage, lymph node metastasis, and poor overall survival.
Article
Oncology
Ayechew A. Getu, Ming Zhou, Shi-Yuan Cheng, Ming Tan
Summary: Cancer, a complex and dynamic disease, remains a leading cause of death in humans. The Mammalian Sterile 20-Like Kinase 4 (MST4 or STK26) plays a crucial role in cell migration and polarity, and is involved in various processes such as tumor cell proliferation, migration, invasion, survival, and cancer metastasis. MST4 interacts with PDCD10 to promote tumor growth and migration, and phosphorylates ATG4B to mediate autophagy signaling and contribute to treatment resistance. Overall, MST4 functions as an oncogene and shows potential as a therapeutic target.
Review
Biochemistry & Molecular Biology
Ayechew Adera Getu, Abiye Tigabu, Ming Zhou, Jianrong Lu, Oystein Fodstad, Ming Tan
Summary: B7-H3 is a crucial factor in cancer progression, with selective expression in tumor cells and immune cells. It is involved in tumor cell proliferation, metastasis, and therapeutic resistance. Targeting B7-H3 offers cancer-specific toxicity and minimal harm to healthy cells, making it a promising target for cancer therapy.
Article
Cell Biology
Mengna Li, Yanmei Wei, Yukun Liu, Jianxia Wei, Xiangting Zhou, Yumei Duan, Shipeng Chen, Changning Xue, Yuting Zhan, Lemei Zheng, Hongyu Deng, Faqing Tang, Songqing Fan, Wei Xiong, Guiyuan Li, Ming Tan, Ming Zhou
Summary: BRD7 functions as a tumor suppressor by negatively regulating the enhancer activity and expression of BIRC2 in nasopharyngeal carcinoma. BIRC2 promotes tumor growth and metastasis, and its expression is negatively correlated with BRD7 expression in NPC tissues. Targeting the BRD7/BIRC2 regulation axis could be a potential strategy for NPC diagnosis and treatment.
CELL DEATH & DISEASE
(2023)
Review
Cell Biology
Timofey Lebedev, Rubina Kousar, Bbumba Patrick, Muhammad Usama, Meng-Kuei Lee, Ming Tan, Xing-Guo Li
Summary: Epigenetic remodeling and metabolic reprogramming are two highly intertwined cancer hallmarks. Recent studies have shown that the interplay between epigenetic regulation and metabolic rewiring can be targeted as a potential Achilles' heel in cancer. This review explores the immunomodulatory role of ARID1A and summarizes the advances in targeting ARID1A-deficient cancers to improve patient outcome by harnessing the immune-metabolic vulnerability.
Article
Biochemistry & Molecular Biology
Fang-Ju Cheng, Chien-Yi Ho, Tzong-Shiun Li, Yeh Chen, Yi-Lun Yeh, Ya-Ling Wei, Thanh Kieu Huynh, Bo-Rong Chen, Hung-Yu Ko, Chen-Si Hsueh, Ming Tan, Yang-Chang Wu, Hui-Chi Huang, Chih-Hsin Tang, Chia-Hung Chen, Chih-Yen Tu, Wei-Chien Huang
Summary: Two phytochemicals found in Artemisia argyi, eriodictyol and umbelliferone, have been shown to suppress the cellular entry of SARS-CoV-2 by preventing the binding of the S protein to ACE2. Umbelliferone also effectively prevents inflammation in lung tissues caused by SARS-CoV-2 infection.
CELL AND BIOSCIENCE
(2023)
Review
Oncology
Khanisyah Erza Gumilar, Yeh Chin, Ibrahim Haruna Ibrahim, Brahmana A. Tjokroprawiro, Jer-Yen Yang, Ming Zhou, Natalie R. Gassman, Ming Tan
Summary: Heat shock factor 1 (HSF1) is a crucial transcription factor involved in regulating cellular heat shock response (HSR). It activates heat shock proteins (HSPs) as chaperones to correct protein folding and maintain proteostasis in response to proteotoxic stress. In addition to its role in HSR, HSF1 is often overexpressed in various cancer cells, promoting malignancy and indicating a poor prognosis. The mechanisms of HSF1-induced tumorigenesis are complex and depend on the type of cancer. Targeting HSF1 provides a novel strategy for cancer treatment.
Review
Medicine, Research & Experimental
Yeh Chin, Khanisyah E. Gumilar, Xing-Guo Li, Brahmana A. Tjokroprawiro, Chien-Hsing Lu, Jianrong Lu, Ming Zhou, Robert W. Sobol, Ming Tan
Summary: HSF1 is a master regulator of heat shock responsive signaling and also regulates a non-heat shock responsive transcriptional network. It plays important roles in cellular transformation and cancer development. Research on HSF1 has been active due to its critical functions in handling stressful cellular states. New functions and molecular mechanisms have been continuously discovered, providing new targets for cancer treatment strategies. This article reviews the essential roles and mechanisms of HSF1 in cancer cells, focusing on recently discovered functions and their underlying mechanisms, as well as advances in HSF1 inhibitors for cancer drug development.
Review
Oncology
Jingshan Huang, Ming Tan
Summary: Artificial intelligence tools like ChatGPT provide scientists with an exciting opportunity to simplify their research and produce impactful articles. By using ChatGPT, scientists can greatly enhance the efficiency and quality of writing review articles. It speeds up writing, develops outlines, adds details, and improves writing style. However, caution must be taken as ChatGPT has limitations, and generated text should be reviewed and edited to avoid plagiarism and fabrication. Despite these limitations, ChatGPT is a powerful tool that allows scientists to focus on analyzing and interpreting literature reviews.
AMERICAN JOURNAL OF CANCER RESEARCH
(2023)
