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Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from A data-driven Perspective

Genomics, Proteomics & Bioinformatics 2023年第1期21卷 164-176页

作者： Jianlei Gu Jiawei Dai Hui Lu Hongyu Zhao SJTU-Yale Joint Center for Biostatistics and Data Science Department of Bioinformatics and BiostatisticsSchool of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghai 200240China Center for Biomedical Informatics Shanghai Engineering Research Center for Big Data in Pediatric Precision MedicineShanghai Children’s HospitalShanghai 200040China Department of Biostatistics Yale UniversityNew HavenCT 06511USA

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human *** expressed genes(UEGs)refer to the genes expressed across a majority of,if not all,phenotypic and physiological conditions of an *** is known that many human genes are broadly expressed across ***,most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns,thus limiting the potential use of UEG *** this study,we proposed a novel data-driven framework to leverage the extensive collection of40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns,which offers a valuable resource to further characterize human *** results suggest that about half(12,234;49.01%)of the human genes are expressed in at least 80%of human transcriptomes,and the median size of the human transcriptome is 16,342 genes(65.44%).Through gene clustering,we identified a set of UEGs,named LoVarUEGs,which have stable expression across human transcriptomes and can be used as internal reference genes for expression *** further demonstrate the usefulness of this resource,we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns,suggesting that the repression of these genes may not be unique to islet beta cells.

关键词： Ubiquitous expression Housekeeping gene Disallowed gene Expression specificity Expression variability

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The Digital Twin City in Enhancing Flood Evacuation Systems: Future Opportunities and Challenges

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IEEE Access 2025年 13卷 32371-32383页

作者： Setijadi Prihatmanto, Ary Prasetyadi, Abdurrakhman Yoganingrum, Ambar Sutriadi, Ridwan Hadiana, Ana Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung40132 Indonesia National Research and Innovation Agency Research Center for Data and Information Science Bandung40231 Indonesia Bandung Institute of Technology School of Architecture Planning and Policy Development Bandung40132 Indonesia

In recent decades, the increasing frequency and severity of natural disasters have necessitated the development of more effective disaster management systems. This paper explores the potential of digital twin technology to enhance flood evacuation systems. A digital twin-city model can simulate urban environments, predict flood inundation, and identify optimal evacuation routes in real-time. The study conducts a systematic literature review to assess current advancements, evaluating the integration of 3D city models, artificial intelligence, and Internet of things sensors in flood evacuation planning. Results indicate that digital twin technology significantly improves predictive capabilities and evacuation efficiency, although data integration, model accuracy, and computational demands remain. Future research should focus on enhancing data integration, refining simulation models, improving predictive analytics, developing advanced visualization tools, and validating models across diverse environments to ensure reliability and effectiveness. © 2025 The Authors.

关键词： Digital elevation model

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Towards Predictable Process and Consequence Attributes of data-Driven Group Work: Primary Analysis for Assisting Teachers with Automatic Group Formation

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Educational Technology and Society 2023年第4期26卷 90-103页

作者： Liang, Changhao Horikoshi, Izumi Majumdar, Rwitajit Flanagan, Brendan Ogata, Hiroaki Graduate School of Informatics Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Japan Center for Innovative Research and Education in Data Science Kyoto University Japan

data-driven platforms with rich data and learning analytics applications provide immense opportunities to support collaborative learning such as algorithmic group formation systems based on learning logs. However, teachers can still get overwhelmed since they have to manually set the parameters to create groups and it takes time to understand the meaning of each indicator. Therefore, it is imperative to explore predictive indicators for algorithmic group formation to release teachers from the dilemma with explainable group formation indicators and recommended settings based on group work purposes. Employing learning logs of group work from a reading-based university course, this study examines how learner indicators from different dimensions before the group work connect to the subsequent group work processes and consequences attributes through correlation analysis. Results find that the reading engagement and previous peer ratings can reveal individual achievement of the group work, and a homogeneous grouping strategy based on reading annotations and previous group work experience can predict desirable group performance for this learning context. In addition, it also proposes the potential of automatic group formation with recommended parameter settings that leverage the results of predictive indicators. © (2023). All Rights Reserved.

关键词： Correlation analysis CSCL GLOBE Group formation Group work indicator Group work prediction Teacher assistance

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Digital Avatar Sub-Metaverse Modeling Using Terrestrial Photogrammetry Techniques 10

Digital Avatar Sub-Metaverse Modeling Using Terrestrial Phot...

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10th International Conference on Computer, Control, informatics and its Applications, IC3INA 2023

作者： Prasetyadi, Abdurrakhman Rezaldi, Muhammad Yudhi Trianggoro, Cahyo Febriandirza, Arafat Suhud, Ridwan Gunawan, Aang Ramdhan, Haidaruddin Muhammad National Research and Innovation Agency Research Center for Data and Information Science Bandung Indonesia Telkom University Faculty of Informatics Bandung Indonesia

ISBN: (纸本)9798350394870

In this study, we explore the metaverse, a virtual realm blending the digital and real worlds. The metaverse promises immersive experiences, and we focus on creating lifelike avatars and environments within a scientific hub called the science and Technology Region (KST). We use a method called terrestrial photogrammetry to make 3D avatars, focusing on researchers at KST. The results show that Agisoft Metashape makes highly precise 3D models with symmetrical details, while the KIRI Engine is faster in processing. These findings suggest that we can make better avatars and environments in the metaverse, but the choice between precision and speed depends on the specific application. © 2023 IEEE.

关键词： Blending

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The Fine-Grained Complexity of Approximately Counting Proper Connected Colorings (Extended Abstract) 16th

The Fine-Grained Complexity of Approximately Counting Prope...

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16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023

作者： Barish, Robert D. Shibuya, Tetsuo Division of Medical Data Informatics Human Genome Center Institute of Medical Science University of Tokyo 4-6-1 Shirokanedai Minato-ku Tokyo108-8639 Japan

ISBN: (纸本)9783031496134

A k-proper connected 2-coloring for a graph is an edge bipartition which ensures the existence of at least k vertex disjoint simple alternating paths (i.e., paths where no two adjacent edges belong to the same partition) between all pairs of vertices. In this work, for every k∈ N> 0, we show that exactly counting such colorings is # P -hard under many-one counting reductions, as well as # P -complete under many-one counting reductions for k= 1. Furthermore, for every k∈ N> 0, we rule out the existence of a 2o(nk2) time algorithm for finding a k-proper connected 2-coloring of an order n graph under the ETH, or for exactly counting such colorings assuming the moderated Counting Exponential Time Hypothesis (#ETH) of (Dell et al.;ACM Trans. Algorithms 10(4);2014). Finally, assuming the Exponential Time Hypothesis (ETH), and as a consequence of a recent result of (Dell & Lapinskas;ACM Trans. Comput. Theory 13(2);2021), for every k∈ N> 0 and every ϵ> 0, we are able to rule out the existence of a 2o(nk2)/ϵ2 time algorithm for approximating the number of k-proper connected 2-colorings of an order n graph within a multiplicative factor of 1 + ϵ. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Coloring

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Internet Service Assessment in Lombok Barat Regency

Internet Service Assessment in Lombok Barat Regency

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2024 International Conference on Information Technology Systems and Innovation, ICITSI 2024

作者： Sumirah Nugroho, Budi Grahitandaru, Andrari Office of Communication Informatics and Statistics West Lombok West Lombok Regency Indonesia Res. Center for Data and Information Science Research and Innovation National Agency Bandung Indonesia

ISBN: (纸本)9798331511470

The rapid development of digital technology has significantly transformed governance, mainly through internet services. This study examines internet services governance within the Communication, informatics, and Statistics Office of West Lombok Regency, which strategically supports digital government. While the vast potential of internet services can enhance efficiency, transparency, and accountability, several challenges, such as inadequate regulations, limited human resources, and infrastructure, hinder its complete optimization. Using the Information and Communication Technology governance framework, this research explores the implementation of extensive data management and provides recommendations to strengthen existing governance practices. Additionally, the study focuses on Internet service management, which is essential for improving governance quality and public service delivery. Despite the potential benefits, internet service governance faces similar challenges, particularly regarding uneven bandwidth distribution among government offices. This imbalance results in inefficiencies, with some offices lacking sufficient resources to operate effectively, leading to administrative delays and disruptions in service delivery. The research uses descriptive statistical analysis to evaluate data from 44 government offices, assessing user numbers, bandwidth allocation, and usage efficiency. Linear regression and k-means clustering are applied to model internet service maturity and classify offices based on usage patterns. The findings reveal substantial disparities in user numbers, bandwidth distribution, and efficiency ratios, with average users and bandwidth standing at 108.02 and 166.14 mbps, respectively. Clustering analysis identified three primary groups, emphasizing the need for further assessment to improve bandwidth allocation and ensure fair distribution based on each agency's specific requirements. © 2024 IEEE.

关键词： Efficiency

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Chatbots and EFL Learning: A Systematic Review

Chatbots and EFL Learning: A Systematic Review

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2024 Joint of International Conference on Learning Analytics and Knowledge Workshops, LAK-WS 2024

作者： Woollaston, Steve Flanagan, Brendan Ogata, Hiroaki Graduate School of Social Informatics Kyoto University Kyoto Japan Center for Innovative Research and Education in Data Science Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Kyoto Japan

Chatbots have been increasingly playing a greater role in English as a foreign language education, offering learners the opportunity to practise with a conversational agent at any time and in different contexts. To grasp how this field has developed and identify emerging trends and opportunities, we conducted a systematic bibliometric analysis of research on chatbots in English language learning from 2006 to 2023. The analysis highlights the increasing importance of Large Language Models in language learning, exploring their potential to overcome previous limitations of chatbot technology. The implications of these findings for future research are discussed, particularly the potential for chatbot designs tailored to the specific needs of English language learners. © 2024 CEUR-WS. All rights reserved.

关键词： Speech processing

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MAML^(2):meta reinforcement learning via meta-learning for task categories

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Frontiers of Computer science 2023年第4期17卷 57-67页

作者： Qiming FU Zhechao WANG Nengwei FANG Bin XING Xiao ZHANG Jianping CHEN School of Electronics and Information Engineering Suzhou University of Science and TechnologySuzhou 215009China Chongqing Industrial Big Data Innovation Center Co.Ltd. Chongqing 404100China School of Medical Informatics Xuzhou Medical UniversityXuzhou 221004China School of Architecture and Urban Planning Suzhou University of Science and TechnologySuzhou 215009China

Meta-learning has been widely applied to solving few-shot reinforcement learning problems,where we hope to obtain an agent that can learn quickly in a new ***,these algorithms often ignore some isolated tasks in pursuit of the average performance,which may result in negative adaptation in these isolated tasks,and they usually need sufficient learning in a stationary task *** this paper,our algorithm presents a hierarchical framework of double meta-learning,and the whole framework includes classification,meta-learning,and ***,in the classification process,we classify tasks into several task subsets,considered as some categories of tasks,by learned parameters of each task,which can separate out some isolated tasks ***,in the meta-learning process,we learn category parameters in all subsets via ***,based on the gradient of each category parameter in each subset,we use meta-learning again to learn a new metaparameter related to the whole task set,which can be used as an initial parameter for the new ***,in the re-adaption process,we adapt the parameter of the new task with two steps,by the meta-parameter and the appropriate category parameter ***,we demonstrate our algorithm prevents the agent from negative adaptation without losing the average performance for the whole task ***,our algorithm presents a more rapid adaptation process within ***,we show the good performance of our algorithm with fewer samples as the agent is exposed to an online meta-learning setting.

关键词： meta-learning reinforcement learning few-shot learning negative adaptation

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Development of a Natural Language Processing Tool to Extract Acupuncture Point Location Terms 11

Development of a Natural Language Processing Tool to Extract...

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11th IEEE International Conference on Healthcare informatics, ICHI 2023

作者： Li, Yiming Peng, Xueqing Li, Jianfu Peng, Suyuan Pei, Donghong Tao, Cui Xu, Hua Hong, Na The University of Texas Health Science Center at Houston School of Biomedical Informatics HoustonTX United States Yale University Section of Biomedical Informatics and Data Science School of Medicine New HavenCT United States Peking University National Institute of Health Data Science Beijing China The University of Texas Md Anderson Cancer Center HoustonTX United States

ISBN: (纸本)9798350302639

Acupuncture point location information is significant to the effect of acupuncture therapy. A wealth of knowledge related to acupuncture point locations is typically dispersed across books or reports in free-text format, which can pose challenges for machines to understand and facilitate. In this study, our purpose is to develop a natural language processing (NLP) tool to extract acupuncture point location information. We adopted the World Health Organization (WHO) Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our reference standard and corpus. Our proposed approach to develop and validate the NLP tool involves three key steps: 1) We leveraged pre-existing terminologies from the anatomy domain, specifically the International Anatomical Terminology (IAT) and Uber-anatomy Ontology (UBERON), to construct a baseline dictionary of acupoint locations. This dictionary was then used in conjunction with a dictionary lookup method to match terms in the acupuncture location descriptions outlined by the WHO Standard;2) We employed NLP models based on machine learning and deep learning techniques, specifically utilizing Conditional Random Fields (CRFs) and Recurrent Neural Network (RNN) for training. The CRFs and RNN models achieved overall F1 scores of 0.955 and 0.945, respectively;3) We encoded the extracted entities into standardized concepts and enriched the baseline dictionary using these entities. In this study, a customized NLP tool was developed and validated for extracting acupuncture point location terms. This tool can be used in various informatics applications to support acupuncture research, education, and practices. © 2023 IEEE.

关键词： Acupuncture

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IMPROVED STATISTICAL AND COMPUTATIONAL COMPLEXITY OF THE MEAN-FIELD LANGEVIN DYNAMICS UNDER STRUCTURED data 12

IMPROVED STATISTICAL AND COMPUTATIONAL COMPLEXITY OF THE MEA...

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12th International Conference on Learning Representations, ICLR 2024

作者： Nitanda, Atsushi Oko, Kazusato Suzuki, Taiji Wu, Denny IHPC Agency for Science Technology and Research Singapore CFAR Agency for Science Technology and Research Singapore Department of Mathematical Informatics The University of Tokyo Japan Center for Advanced Intelligence Project RIKEN Japan Center for Data Science New York University United States Center for Computational Mathematics Flatiron Institute United States

Recent works have shown that neural networks optimized by gradient-based methods can adapt to sparse or low-dimensional target functions through feature learning;an often studied target is the sparse parity function on the unit hypercube. However, such isotropic data setting does not capture the anisotropy and low intrinsic dimensionality exhibited in realistic datasets. In this work, we address this shortcoming by studying how gradient-based feature learning interacts with structured (anisotropic) input data: we consider the classification of k-sparse parity on high-dimensional orthotope where the feature coordinates have varying magnitudes, and analyze the learning complexity of the mean-field Langevin dynamics (MFLD), which describes the noisy gradient descent update on two-layer neural network. We show that the statistical complexity (i.e. sample size) and computational complexity (i.e. network width) of MFLD can both be improved when prominent directions of the anisotropic input data align with the support of the target function. Moreover, by employing a coordinate transform determined by the gradient covariance, the width can be made independent of the target degree k. Lastly, we demonstrate the benefit of feature learning by establishing a kernel lower bound on the classification error, which applies to neural networks in the lazy regime. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Computational complexity

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