Article
Computer Science, Information Systems
Zhanbo Lin, Zhilin Yao, Shengsheng Wang, Whenzhuo Song
Summary: Signed social recommendations leverage signed social information to solve the cold-start and data sparsity problem. Graph Neural Network methods have shown powerful performance in graph representation learning and have motivated the development of GNN-based social recommendation frameworks. However, building GNN-based signed social recommender systems faces challenges, such as the social inconsistency problem. To address this, the authors propose a novel framework called ESSRec that reconstructs the signed social graph and improves the performance of GNNs.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Daniela Oliveira, Mathieu d'Aquin
Summary: Knowledge Graphs are important in aggregating and publishing knowledge on the Web. This paper proposes the RICDaM framework to facilitate the selection of a data model by generating and ranking candidates that match entity types and properties. Experiments using datasets from the library domain show that this methodology can produce meaningful candidate data models.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Astronomy & Astrophysics
V. H. F. Neo, J. Zinke, T. Fung, C. J. Merchant, K. J. A. Zawada, H. Krawczyk, J. M. Maina
Summary: Coral reefs are at risk of accelerated decline due to climate change-induced changes, and it is uncertain if the Sea Surface Temperature data used for coral reef studies are consistent among different data products. Understanding the consistency among different SST data sources can help improve monitoring and understanding of the impact of global warming on coral reefs. The study compares four types of SST data and highlights the need to compare existing indicators of thermal stress from different data sets. Rating: 8/10
EARTH AND SPACE SCIENCE
(2023)
Article
Geochemistry & Geophysics
Shi Liu, Banghai Wu, Cheng-Zhi Zou, Yu Wang
Summary: In this study, a continuous and consistent climate data record (FCDR) was developed using satellite observations. The FCDR was based on a multichannel brightness temperature data from multiple satellites, and was corrected for hardware differences and intercalibrated to ensure accuracy. The resulting FCDR provided a long-term record of climate variables, such as column water vapor, and demonstrated high potential for climate research.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Multidisciplinary Sciences
Elise Acheson, Ross S. Purves
Summary: Scientific articles often include geographic information, but in natural language without machine-readable metadata. Automatically extracting this information can help with meta-analyses and identifying geographic research gaps.
Article
Computer Science, Information Systems
Claudia Diannantini, Paolo Lo Giudice, Domenico Potena, Emanuele Storti, Domenico Ursino
Summary: Data lakes have emerged as an effective support for extracting information and knowledge from highly heterogeneous and rapidly changing data sources. However, managing data lakes requires new techniques. This paper introduces a network-based model to represent structured, semi-structured, and unstructured sources of a data lake, and proposes a new approach for extracting topic-guided views.
INFORMATION SYSTEMS FRONTIERS
(2021)
Article
Materials Science, Multidisciplinary
Zhanchao Huang, Shaohan Huang, Junyin Li, Yong Wang, Hanqing Jiang
Summary: This article introduces a method for extracting hidden conservative equations from nonconservative state data without any excitation information. The method involves embedding Euler-Lagrangian equations, orthogonalizing to eliminate the influence of nonconservative factors, and extracting Lagrangians for discrete or continuous systems, achieving simplicity in complex systems.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2023)
Article
Engineering, Mechanical
Huimei Ma, Xiaofan Lu, Linan Zhang
Summary: In this paper, a data-driven regression approach is proposed to identify parametric governing equations from time-series data. Iterative computations are performed for each time stamp to determine if the governing equations to be recovered are time dependent. The results are then used to extract the parametric equations. The proposed method outperforms other sparse-promoting algorithms in identifying parametric differential equations in the low-noise regime in terms of accuracy and computation time.
NONLINEAR DYNAMICS
(2023)
Article
Engineering, Marine
Zhaojin Yan, Liang Cheng, Rong He, Hui Yang
Summary: This study proposes a method for extracting ship stopping information based on ship trajectory features and geographic semantics. By excavating trajectory features, the stopping points in the port area are recognized, and a classification model for ship stopping is constructed. Experimental results show that this method can effectively extract ship stopping information and provide support for ship behavior understanding and ship traffic analysis.
Article
Biochemistry & Molecular Biology
Mingjie Luo, Yinqiu Ji, David Warton, Douglas W. Yu
Summary: Accurately extracting species-abundance information from DNA-based data is important for various applications. This study focuses on distinguishing within-sample across-species quantification and across-sample within-species quantification. The authors review literature on methods to remove biases and noise in DNA-based data sets and propose using DNA spike-ins as well as a model-based estimator to correct for pipeline noise.
MOLECULAR ECOLOGY RESOURCES
(2023)
Article
Ergonomics
Davide Maggi, Richard Romano, Oliver Carsten
Summary: The study found that drivers' steering engagement is more influenced by the transition initiation rather than the quality of guidance. In user-initiated transitions, drivers exert stronger steering inputs, allowing them to maintain larger TTLC values with fewer corrections.
ACCIDENT ANALYSIS AND PREVENTION
(2022)
Article
Multidisciplinary Sciences
T. Metz, M. Koch, P. Lenz
Summary: Estimating and predicting future microplastic distributions is a major challenge in microplastic research, but can only be achieved with enhanced understanding of individual microplastic particle decay. Currently available size distribution data does not provide useful insights, however, collecting time series data at identical spots and combining size measurements with mass measurements can extract flux rates and decay parameters of individual particles.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Analytical
Isabel Ten-Domencech, Marta Moreno-Torres, Jose Vicene Castell, Guillermo Quintas, Julia Kuligowski
Summary: Extracting meaningful biological information from metabolomics data is challenging, but the Mantel test can help assess the significance of correlation in metabolic pathway analysis. It allows critical comparisons between different phenotypes, studies, and methods, aiding data interpretation and meta-analysis.
ANALYTICA CHIMICA ACTA
(2021)
Article
Multidisciplinary Sciences
Anca Flavia Savulescu, Emmanuel Bouilhol, Nicolas Beaume, Macha Nikolski
Summary: RNA subcellular localization has been recognized as a common phenomenon that can be characterized using sequence features and microscopy images. While imaging data is ideal for describing RNA distribution, it is limited to a small number of RNAs due to cost, time, and technical challenges. Additional techniques are needed to complement imaging data for better characterization of RNA localization.
Article
Computer Science, Information Systems
Rik Eshuis
Summary: Data-centric process management enables knowledge workers to perform knowledge-intensive processes flexibly. Process templates, manually modified to suit the context of specific cases, are a key component. Extracting reusable fragments from process variants enhances efficiency and improves the quality of complex data-centric processes.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Biotechnology & Applied Microbiology
Xubin Zheng, Kwong-Sak Leung, Man-Hon Wong, Lixin Cheng
Summary: This study proposed a novel diagnostic strategy using relative expressions of lncRNA pairs to identify a sepsis diagnostic signature. The signature showed better predictive performance across different ages and normalization methods compared to common machine learning models and existing signatures. Functional analysis revealed that the lncRNA pairs in the signature are functionally similar.
Article
Cell Biology
Xubin Zheng, Qiong Wu, Haonan Wu, Kwong-Sak Leung, Man-Hon Wong, Xueyan Liu, Lixin Cheng
Summary: This study introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Differential methylated genes measured by various bisulfite sequencing assays and 450 k beadchip were consistently hypo-methylated in liver cancer with high functional similarity.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Wenbo Wei, Miao Zhang, Zhongyuan Xu, Weifeng Li, Lixin Cheng, Hongbao Cao, Min Ma, Zongzheng Chen
Summary: In this study, a microfluidic array was developed to trap single cells and deliver consistent dynamic biochemical stimulation, which enhanced the understanding of Ca2+ signaling at single cell resolution. The effectiveness of the device was demonstrated through numerical simulation, trajectory analysis, and fluorescent experiments. The device enabled investigation of cellular response to dynamic stimuli at a single cell level.
BIOSCIENCE REPORTS
(2021)
Article
Biochemistry & Molecular Biology
Zhangxiang Zhao, YingYing Guo, Yaoyao Liu, Lichun Sun, Bo Chen, Chengyu Wang, Tingting Chen, Yuquan Wang, Yawei Li, Qi Dong, Liqiang Ai, Ran Wang, Yunyan Gu, Xia Li
Summary: The study individualized lncRNA expression profiles for breast cancer using the LncRNA Individualization method, constructing an individualized differentially expressed lncRNA profile for breast cancer and investigating subtype-specific lncRNAs.
Article
Cell Biology
Tingting Chen, Yingying Guo, Jiayi Wang, Liqiang Ai, Lu Ma, Wenxin He, Zhixin Li, Xiaojiang Yu, Jinrui Li, Xingxing Fan, Yunyan Gu, Haihai Liang
Summary: The study identified a key lncRNA, CTD-2528L19.6, that plays a critical role in regulating fibroblast activation in the progression of idiopathic pulmonary fibrosis (IPF). Results suggest that CTD-2528L19.6 may prevent the progression of IPF and alleviate fibroblast activation during the advanced-stage, providing potential new insights for IPF treatment.
CELL DEATH & DISEASE
(2021)
Article
Biochemical Research Methods
Ran Wang, Xubin Zheng, Jun Wang, Shibiao Wan, Fangda Song, Man Hon Wong, Kwong Sak Leung, Lixin Cheng
Summary: This study introduces a new method called scPAGE, which utilizes single-cell pair-wise gene expression to transfer knowledge across platforms, with applications in acute myeloid leukemia research. The results show that scGPS performs better in bulk RNA-seq classification than traditional gene expression strategies, demonstrating potential in revealing the molecular mechanisms of AML and emphasizing the benefits of gene signature transfer.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Qiong Wu, Xubin Zheng, Kwong-Sak Leung, Man-Hon Wong, Stephen Kwok-Wing Tsui, Lixin Cheng
Summary: This study introduces a novel strategy using DNA methylation and RNA expression data to discriminate hepatocellular carcinoma (HCC). Immune genes with negative correlations between expression and promoter methylation are identified as candidates for HCC detection. A methylation GPS (mGPS) and an expression GPS (eGPS) are separately constructed and then assembled into a meGPS, which successfully detects and predicts HCC with reliable performance validated by independent datasets. This study provides potential molecular targets for the detection and therapy of HCC.
Article
Biology
Haili Li, Xubin Zheng, Jing Gao, Kwong-Sak Leung, Man-Hon Wong, Shu Yang, Yakun Liu, Ming Dong, Huimin Bai, Xiufeng Ye, Lixin Cheng
Summary: The regulation of non-coding RNA is associated with the diagnosis and targeted therapy of complex diseases. By constructing a ceRNA network and using a novel motif, SOC index was found to be negatively correlated with the CD8+/CD4+ ratio in tumor infiltration, reflecting the migration and growth of tumor cells in ovarian cancer progression.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Pharmacology & Pharmacy
Cong Xu, Wanyang Li, Tangzhiming Li, Jie Yuan, Xinli Pang, Tao Liu, Benhui Liang, Lixin Cheng, Xin Sun, Shaohong Dong
Summary: This study constructed a molecular signature of ACS based on iron metabolism-related genes and identified novel iron metabolism gene markers for early stage of ACS. By using Elastic Net algorithm, five genes with optimal performance were screened, and the prediction model can be used for early diagnosis of ACS.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Biochemical Research Methods
Ran Wang, Xubin Zheng, Fangda Song, Man Hon Wong, Kwong Sak Leung, Lixin Cheng
Summary: Human gut microbiota dysbiosis is associated with various diseases, and it is crucial to uncover the associations between gut microbiota and disease states along with other factors. Existing methods may lead to false associations, so we propose a new method to investigate gut microbiota using groups of related taxa instead of individual taxa. The results show that this method can better explain the relationships between gut microbiota and clinical factors, and it demonstrates effectiveness in identifying microbial modules.
Review
Biochemical Research Methods
Jun Wang, Marc Horlacher, Lixin Cheng, Ole Winther
Summary: RNA localization is important for spatial translation regulation, and this review discusses its molecular mechanisms, experimental techniques, and machine learning-based prediction tools. The three main molecular mechanisms controlling RNA localization to distinct cellular compartments, including directed transport, mRNA degradation protection, and diffusion/local entrapment, are reviewed. Advances in experimental methods provide ample data resources for the design of powerful machine learning models in RNA localization prediction. The review also covers publicly available predictive tools, serving as a guide for users and encouraging the development of more effective prediction models. Lastly, an overview of multimodal learning is presented as a potential new avenue for RNA localization prediction.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Engineering, Environmental
Liuzhi Hao, Shuwen Huang, Tongling Huang, Dan Yi, Chenmin Wang, Lixin Cheng, Min Guan, Jun Wu, Di Chen, Haobo Pan, William W. Lu, Xiaoli Zhao
Summary: This study provides a feasible and effective strategy for modifying engineered exosomes to enhance bone regeneration.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Biochemical Research Methods
Lixin Cheng, Haonan Wu, Xubin Zheng, Ning Zhang, Pengfei Zhao, Ran Wang, Qiong Wu, Tao Liu, Xiaojun Yang, Qingshan Geng
Summary: This study developed an ensemble gene pair signature based on the IDH and 1p/19q status, which can serve as an independent predictor for risk stratification and survival prediction in glioma. The results showed that this ensemble signature had higher predictive accuracy compared to other prognostic signatures.
Article
Biochemical Research Methods
Qizhi Li, Xubin Zheng, Jize Xie, Ran Wang, Mengyao Li, Man-Hon Wong, Kwong-Sak Leung, Shuai Li, Qingshan Geng, Lixin Cheng
Summary: A diagnostic model based on host gene expression was used to diagnose acute infections. However, its clinical usage was limited due to small sample sizes. In this study, a large-scale dataset was constructed and analyzed using a sophisticated strategy to build gene pair signatures for bacterial, viral, and noninfected patients. These signatures were further combined into an antibiotic decision model with strong performance in distinguishing bacterial and viral infections.
Article
Biochemistry & Molecular Biology
Qi Dong, Mingyue Liu, Bo Chen, Zhangxiang Zhao, Tingting Chen, Chengyu Wang, Shuping Zhuang, Yawei Li, Yuquan Wang, Liqiang Ai, Yaoyao Liu, Haihai Liang, Lishuang Qi, Yunyan Gu
Summary: PARP inhibitors are designed based on synthetic lethality, aiming to broaden patient benefits and overcome drug resistance. Genetic interactions, such as synthetic lethality and synthetic viability, play a role in drug response. By developing novel computational methods and utilizing functional screens, sensitive and resistant genes related to PARP inhibitors have been identified, providing new insights for precision therapeutics.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
