Article
Business
Marcello M. Mariani, Maria Ek Styven, Frederic Teulon
Summary: Recent data leaks have raised concerns about the security of digital personal data among Internet users, but consumers are increasingly accepting cloud computing empowered Digital Personal Data Stores. Trust is found to be a key factor in enhancing the acceptance of DPDSs, while privacy risk does not moderate the relationship between trust and acceptance.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Computer Science, Information Systems
Yi Su, Dan Feng, Yu Hua, Zhan Shi, Tingwei Zhu
Summary: This article introduces NetRS, a framework for addressing the effectiveness of replica selection algorithms in distributed data storage systems. By leveraging emerging network devices, NetRS supports various replica selection algorithms and is suitable for the network topology of modern data centers. Experimental results show that compared to traditional approaches, NetRS significantly reduces latency and effectively improves response speed even in the presence of unexpected events and network congestion.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Yohann Chasseray, Anne-Marie Barthe-Delanoe, Stephane Negny, Jean-Marc Le Lann
Summary: This article proposes a method for measuring performance in unsupervised context of knowledge extraction. It also presents an unsupervised rule-based approach for domain-independent ontology population and knowledge extraction from textual data.
INFORMATION SCIENCES
(2023)
Article
Green & Sustainable Science & Technology
Xinlei Zhou, Wenye Lin, Ping Cui, Zhenjun Ma, Tishi Huang
Summary: This paper introduces an efficient data mining strategy to analyze the operational data of ground source heat pump systems, revealing inefficient operation patterns and energy conservation opportunities.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Education & Educational Research
Kubra Karakaya-Ozyer, Zeki Yildiz
Summary: The purpose of this study was to develop an electronic performance support system (EPSS) for quantitative data analysis for educational researchers. Through four phases of research, it was found that researchers faced various challenges in quantitative research, and the EPSS system was proven to be helpful in addressing these issues.
EDUCATION AND INFORMATION TECHNOLOGIES
(2022)
Article
Chemistry, Medicinal
Mingju Wen, Jianbo Sun, Miao Yang, Xueling Zhang, Yue Wang, Wen Zhou, Yuning Shi, Yujing Huang, Na Li, Li Chen
Summary: Twelve new hybrid compounds of Esculetin with nitric oxide (NO) donors and/or mitochondrial targeting groups were designed, synthesized, and evaluated for their anti-tumor activity and mechanism in vitro and in vivo. The most potent compound A11 exhibited nanomolar antiproliferative activity on triple-negative breast cancer (TNBC) MDA-MB-231 cells, with a selective inhibitory effect. The mechanism involved mitochondrial targeting, releasing a high concentration of NO, increasing the expression of CypD, and triggering cancer cell apoptosis through increased ROS production, along with cell cycle arrest at the G2/M phase. Moreover, A11 demonstrated superior TNBC inhibition rate and reduced toxicity compared to doxorubicin (DOX) in vivo.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Review
Chemistry, Inorganic & Nuclear
Ramakrishnan Abhijnakrishna, Kuppan Magesh, Agarwal Ayushi, Sivan Velmathi
Summary: The compound 2,2';6,2'' terpyridine has unique properties that have attracted significant interest in various fields. It exhibits intense non-radiative relaxation and low quantum yields, making it valuable in electrochemistry, biochemistry, and photophysical chemistry. Metal-terpyridine complexes have shown great potential in biological activity, acting as anti-tumor and cell imaging agents, as well as effective sensors for recognizing vital biological targets.
COORDINATION CHEMISTRY REVIEWS
(2023)
Article
Computer Science, Artificial Intelligence
Chao-Lung Yang, Thi Phuong Quyen Nguyen
Summary: This paper proposes an integrated data analysis framework that combines unsupervised clustering and supervised classification methods for point-of-sale data analysis. The experimental results show that clustering can reveal the hidden structure of retail store sales performance, while classification can identify the major factors affecting sales performance in different groups of retail stores.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Article
Biochemistry & Molecular Biology
Jayoung Song, Ahreum Kim, Intaek Hong, Sangji Kim, Woong Sub Byun, Hyun Soo Lee, Hyung Sik Kim, Sang Kook Lee, Yongseok Kwon
Summary: In this study, atropisomeric 8-aryltetrahydroisoquinolines were synthesized and evaluated for their biological activities. A highly bioactive racemic compound was produced, showing high antiproliferative activities against various cancer cell lines, including docetaxel-resistant breast cancer cell lines. Each enantiomer could be selectively synthesized using chiral phosphoric acid-catalyzed atroposelective Pictet-Spengler cyclization. The (R)-enantiomer exhibited higher biological activity compared to the (S)-enantiomer and overcame docetaxel resistance in triple-negative breast cancer cell lines via downregulation of STAT3 activation, inducing cellular apoptosis.
BIOORGANIC CHEMISTRY
(2023)
Article
Biochemical Research Methods
Pieter Verschaffelt, James Collier, Alexander Botzki, Lennart Martens, Peter Dawyndt, Bart Mesuere
Summary: The Unipept Visualizations library is a JavaScript package that generates interactive visualizations of both hierarchical and non-hierarchical quantitative data, with support for different visualizations and utilizing the D3.js library.
Article
Mathematics
Raul Estrada-Valenciano, Victor Muniz-Sanchez, Hector De-la-Torre-Gutierrez
Summary: This paper proposes the first entity-matching system for product comparison in Spanish-speaking e-commerce, utilizing image and textual description as matching features and employing advanced techniques in natural language processing and machine learning, achieving significant results.
Article
Construction & Building Technology
Cheng Yang, Jia-Rui Lin, Ke-Xiao Yan, Yi-Chuan Deng, Zhen-Zhong Hu, Cheng Liu
Summary: This paper proposes a data-driven approach to quantitatively evaluate the performance of construction supervisors by integrating analytic hierarchy process (AHP) and activity tracking.
Review
Biochemical Research Methods
Ai Ni, Li-Xuan Qin
Summary: One key feature of transcriptomics data is handling effects, which have a significant impact on survival prediction. Among various normalization methods, quantile normalization tends to underperform compared to median normalization and variance stabilizing normalization in survival prediction. It is important to evaluate normalization methods in the context of downstream analysis and applying median normalization may improve the development of survival predictors.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Transportation
Si Chen, Xiang Yan, Haozhi Pan, Brian Deal
Summary: This paper evaluates the last mile performance of public transportation using an accessibility-based approach, finding high variance in last mile performance in Chicago, with areas of low performance typically clustering in economically disadvantaged areas. Income levels and housing sale price are positively related to last mile performance.
TRAVEL BEHAVIOUR AND SOCIETY
(2021)
Article
Chemistry, Analytical
Mahmoud Abd Rabbou, Mohamed Abdelazeem, Salem Morsy
Summary: The research developed new precise point positioning (PPP) processing models using triple-frequency GPS/Galileo observations, which significantly improved the positioning accuracy for both static and kinematic applications compared to the dual-frequency models.
Article
Computer Science, Information Systems
Li Chen, Dongxin Lu, Menghao Zhu, Muhammad Muzammal, Oluwarotimi Williams Samuel, Guixin Huang, Weinan Li, Hongyan Wu
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
(2019)
Article
Multidisciplinary Sciences
Atsuko Yamaguchi, Yasunori Yamamoto
Article
Biochemical Research Methods
Anne Morgat, Thierry Lombardot, Elisabeth Coudert, Kristian Axelsen, Teresa Batista Neto, Sebastien Gehant, Parit Bansal, Jerven Bolleman, Elisabeth Gasteiger, Edouard de Castro, Delphine Baratin, Monica Pozzato, Ioannis Xenarios, Sylvain Poux, Nicole Redaschi, Alan Bridge
Article
Biology
Jerven Bolleman, Edouard de Castro, Delphine Baratin, Sebastien Gehant, Beatrice A. Cuche, Andrea H. Auchincloss, Elisabeth Coudert, Chantal Hulo, Patrick Masson, Ivo Pedruzzi, Catherine Rivoire, Ioannis Xenarios, Nicole Redaschi, Alan Bridge
Article
Computer Science, Artificial Intelligence
Chaojie Ji, Hongyan Wu
Article
Biotechnology & Applied Microbiology
Rongxiang Zhu, Chaojie Ji, Yingying Wang, Yunpeng Cai, Hongyan Wu
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2020)
Article
Biochemistry & Molecular Biology
Marc Feuermann, Emmanuel Boutet, Anne Morgat, Kristian B. Axelsen, Parit Bansal, Jerven Bolleman, Edouard de Castro, Elisabeth Coudert, Elisabeth Gasteiger, Sebastien Gehant, Damien Lieberherr, Thierry Lombardot, Teresa B. Neto, Ivo Pedruzzi, Sylvain Poux, Monica Pozzato, Nicole Redaschi, Alan Bridge
Summary: UniProtKB is a comprehensive and freely accessible resource that covers natural products from various plants and microorganisms, users can search protein knowledge relevant to natural products through interactive or programmatic queries, and enrich other natural product datasets and databases by mining UniProtKB data.
Article
Genetics & Heredity
Toyofumi Fujiwara, Jae-Moon Shin, Atsuko Yamaguchi
Summary: This paper describes notable updates regarding PubCaseFinder, the GeneYenta matching algorithm, and the PubCaseFinder API. The updated PubCaseFinder and new API empower patient repositories and medical professionals to actively use HPO-based resources.
Article
Computer Science, Artificial Intelligence
Chaojie Ji, Ruxin Wang, Hongyan Wu
Summary: This paper proposes a novel post hoc framework called TraP2, which is based on local fidelity and can generate high-fidelity explanations for any trained GNNs. By incorporating translation, perturbation, and paraphrase layers, TraP2 can effectively highlight the relevant graph structure and important features inside each node, leading to highly faithful explanations.
Article
Biochemical Research Methods
Hongwei Chen, Yunpeng Cai, Chaojie Ji, Gurudeeban Selvaraj, Dongqing Wei, Hongyan Wu
Summary: We propose an adaptive convolution graph network, AdaPPI, to predict protein functional modules in protein-protein interaction networks. By integrating protein gene ontology attributes and network topology, our framework outperforms existing methods in finding functional modules.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Chaojie Ji, Yijia Zheng, Ruxin Wang, Yunpeng Cai, Hongyan Wu
Summary: In this study, a novel molecular optimization paradigm called Graph Polish is proposed. It predicts the optimization center and optimizes the surrounding regions to achieve molecular optimization. An effective learning framework called Teacher and Student Polish captures the dependencies in the optimization steps. Experimental results show that the proposed approach outperforms state-of-the-art methods in multiple optimization tasks and has good explainability and time savings.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Jie Zhang, Yishan Du, Pengfei Zhou, Jinru Ding, Shuai Xia, Qian Wang, Feiyang Chen, Mu Zhou, Xuemei Zhang, Weifeng Wang, Hongyan Wu, Lu Lu, Shaoting Zhang
Summary: The study proposes a graph-based method, DeepAAI, for predicting neutralization activity of antibodies and applies it to recommend probable antibodies for human immunodeficiency virus, severe acute respiratory syndrome coronavirus 2, influenza, and dengue. DeepAAI learns dynamic representations and relation graphs to optimize downstream tasks such as neutralization prediction and concentration estimation. The method demonstrates good performance and rich interpretability, suggesting potential broad-spectrum antibodies against new viral variants.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Mathematical & Computational Biology
Philippe Le Mercier, Jerven Bolleman, Edouard de Castro, Elisabeth Gasteiger, Parit Bansal, Andrea H. Auchincloss, Emmanuel Boutet, Lionel Breuza, Cristina Casals-Casas, Anne Estreicher, Marc Feuermann, Damien Lieberherr, Catherine Rivoire, Ivo Pedruzzi, Nicole Redaschi, Alan Bridge
Summary: SwissBioPics is a freely accessible resource that provides interactive, high-resolution cell images for visualizing subcellular location data. The images cover various cell types from different kingdoms of life and are tagged with unique identifiers from the controlled vocabulary of UniProt. Users can search and explore the cell images through the website and embed them in their own websites using the provided web component. SwissBioPics is also used by UniProt to visualize the subcellular locations and organelles where proteins function.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Atsuko Yamaguchi, Tatsuya Kushida, Yasunori Yamamoto, Kouji Kozaki
SEMANTIC TECHNOLOGY, JIST 2019
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Shuyuan Chen, Chaojie Ji, Ruxin Wang, Hongyan Wu
2020 5TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND ARTIFICIAL INTELLIGENCE (ICMAI 2020)
(2020)