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Collaborative Framework for circRNA-Disease Associations Prediction using Dual Variational Graph

IEEE Transactions on Big Data 2025年

作者： Liu, Changchun Wang, Lei Zhao, Bowei Wei, Mengmeng Li, Yang Lu, Mianshuo Wei, Yu Liang, Sizhe The School of Computer Science and Technology China University of Mining and Technology Xuzhou221116 China Key Lab of Human-machine Interaction and Intelligent Decision Guangxi Acad emy of Science Nanning530007 China The School of Computer Science and Information Engineer ing Hefei University of Technology Hefei230601 China The College of Computer and Information Science School of Software University of Chinese Academy of Sciences Urumqi830011 China

Many experiments have shown that circular RNA (circRNA) can act as biomarkers for complex diseases and play significant regulatory roles in multiple pathological processes. However, most circRNA-disease associations remain unknown, and discovering these associations through biological experimental approach is expensive and time-consuming. Taking into account the shortcomings of current methods, we introduce a new collaborative framework that utilizes multi-heterogeneous graphs, along with variational graph auto-encoders (VGAE) to predict associations between circRNA and diseases. First, we build multi-similarity networks using various biological attributes of circRNA and diseases, and integrate these similarity networks. Two subnetworks are constructed from association matrix and combined similarity network, which included a circRNA-based network and a disease-based network. We then employ random walk with restart and Singular Value Decomposition, for feature extraction from the similarity matrix. Finally, we use collaborative framework to predict the circRNA-disease association scores based on the two subnetworks. We integrate the two score matrices to obtain a final prediction scoring matrix. Using 5-fold cross-validation on the CircR2Disease dataset, our model achieved an AUC score of 0.9828 and an AUPR score of 0.9820. Additionally, among the top 30 highest-scoring circRNA-disease association pairs, 26 associations have already been validated. Our model shows strong performance and can accurately predict associations between circRNA and diseases, according to experimental results. © 2015 IEEE. All rights reserved.

关键词： Variational techniques

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Interactive multi-scale structures for summarizing video content

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Science China(Information Sciences) 2013年第5期56卷 103-114页

作者： WANG HongAn MA CuiXia State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of Sciences Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences

Efficient video summarization leads to facilely exploring video content appropriate to the user’s intention with low cognitive *** this paper,we present a novel approach for summarizing videos in the form of multi-scale structures that exhibit different video features at different scale levels and allow exploration of video contents with multi-scale *** semantic relationship between structures is addressed and user intention is also considered and integrated in the summarization and *** paper first introduces the concept of multi-scale structures for summarizing video content and describes three different types of structures that present important features at different scale ***,a continuous zooming interaction for browsing multi-scale structures is provided to facilitate video ***,an elaborate user study is conducted showing that user performance on understanding and browsing videos is improved.

关键词： multi-scale video summarization sketch visualization interaction

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An approach to visual analysis for task flow management

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Science China(Information Sciences) 2013年第5期56卷 91-102页

作者： TENG DongXing SONG ShaoLei YANG HaiYan MA CuiXia WANG HongAn DAI GuoZhong Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Efficient management of task flow plays an important role in prediction,planning,control and optimization of *** this paper,according to major indicators to evaluate during task flow management such as time performance,resource allocation efficiency and executory costs we establish a task flow management oriented business model and analyze important operations performed in evaluation,analysis,and optimization of task *** on the business model,in the view of problems from multi-source and heterogeneous data without standardized description,we define a unified data model to give a description for the massive and heterogeneous task flow *** we further demonstrate a complex task flow oriented visualization morphology design,with corresponding layout algorithm,and introduce the Focus + Context technique to assist users in analyzing task flows and making accurate ***,we develop a task flow management oriented visual analysis prototype system,and apply it into medical process *** results show that this system can effectively support analysis and evaluation of execution progress,time performance,resource utilization,cost,etc.,which can improve efficiency of the task flow management and contribute to quick and accurate decision-making.

关键词： process management information visualization visual analytics human-computer interaction

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An exploratory study of multimodal interaction modeling based on neural computation

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Science China(Information Sciences) 2016年第9期59卷 63-78页

作者： Lu LU Fei LYU Feng TIAN Yineng CHEN Guozhong DAI Hongan WANG Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences University of Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of Sciences

Multimodal interaction serves an important role in human-computer interaction. In this paper we propose a multimodal interaction model based on the latest cognitive research findings. The proposed model combines two proven neural computations, and helps to reveal the enhancement or depression influence of multimodal presentation upon the corresponding interaction task performance. A set of experiments is designed and conducted within the constraints of the model, which demonstrates the observed performance enhancement and depression effects. Our exploration and the experimental results help to further solve the question about how tactile feedback signal contribute the multimodal interaction efficiency which could provide guidelines for designing the tactile feedback in multimodal interaction.

关键词： human-computer interaction multimodal integration interaction model touch-included interac tion cognition multisensory integration neural computation brain coding

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Emotional tone-based audio continuous emotion recognition 21

Emotional tone-based audio continuous emotion recognition

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Liu, Mengmeng Chen, Hui Li, Yang Zhang, Fengjun Beijing Key Lab of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783319144412

Understanding human emotions in natural communication is still a challenge problem to be solved in human-computer interaction. Emotional tone that people feel within a period of time can affect the way people communicate with others or environment. In this paper, a new emotional tone-based two-stage algorithm for continuous emotion recognition from audio signals is presented. Gaussian mixture models of hidden Markov models (GMM-HMMs) are employed to infer the dimensional emotional tone and affect labels. Two emotional tones, positive or negative, which represent the overall emotion state over an audio clip are first obtained. Then, based on that emotional tone, corresponding positive or negative GMM-HMM classifier is refined to finish the continuous emotion recognition. The experimental results show that our method outperforms the GMM-HMM and SVR in baseline for the Audio-Visual Emotion Challenge (AVEC 2014) database [1]. © Springer International Publishing Switzerland 2015.

关键词： Emotion Recognition

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Gesture interaction in virtual reality

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Virtual Reality & Intelligent Hardware 2019年第1期1卷 84-112页

作者： Yang LI Jin HUANG Feng TIAN Hong-An WANG Guo-Zhong DAI Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of SciencesBeijing 100190China State Key Laboratory of Computer Science Chinese Academy of SciencesBeijing 100190China

With the development of virtual reality(VR)and human-computer interaction technology,how to use natural and efficient interaction methods in the virtual environment has become a hot topic of *** is one of the most important communication methods of human beings,which can effectively express users'*** the past few decades,gesture-based interaction has made significant *** article focuses on the gesture interaction technology and discusses the definition and classification of gestures,input devices for gesture interaction,and gesture interaction recognition *** application of gesture interaction technology in virtual reality is studied,the existing problems in the current gesture interaction are summarized,and the future development is prospected.

关键词： Virtual reality Gesture interaction Gesture recognition

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Constrained maximum weighted bipartite matching:a novel approach to radio broadcast scheduling

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Science China(Information Sciences) 2019年第7期62卷 156-169页

作者： Shaojiang WANG Tianyong WU Yuan YAO Dongbo BU Shaowei CAI State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences Beijing Key Lab of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences

Given a set of radio broadcast programs, the radio broadcast scheduling problem is to allocate a set of devices to transmit the programs to achieve the optimal sound quality. In this article, we propose a complete algorithm to solve the problem, which is based on a branch-and-bound(BnB) algorithm. We formulate the problem with a new model, called constrained maximum weighted bipartite matching(CMBM),i.e., the maximum matching problem on a weighted bipartite graph with constraints. For the reduced matching problem, we propose a novel BnB algorithm by introducing three new strategies, including the highest quality first, the least conflict first and the more edge first. We also establish an upper bound estimating function for pruning the search space of the algorithm. The experimental results show that our new algorithm can quickly find the optimal solution for the radio broadcast scheduling problem at small scales, and has higher scalability for the problems at large scales than the existing complete algorithm.

关键词： radio broadcast scheduling branch-and-bound algorithm constrained maximum weighted bipartite matching Kuhn-Munkres algorithm strategy combinations

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Non-Frontal Facial Expression Recognition Using a Depth-Patch Based Deep Neural Network

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Journal of computer Science & Technology 2017年第6期32卷 1172-1185页

作者： Nai-Ming Yao Hui Chen Qing-Pei Guo Hong-An Wang Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Bcijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China

The challenge of coping with non-frontal head poses during facial expression recognition results in considerable reduction of accuracy and robustness when capturing expressions that occur during natural communications. In this paper, we attempt to recognize facial expressions under poses with large rotation angles from 2D videos. A depth^patch based 4D expression representation model is proposed. It was reconstructed from 2D dynamic images for delineating continuous spatial changes and temporal context under non-frontal cases. Furthermore, we present an effective deep neural network classifier, which can accurately capture pose-variant expression features from the depth patches and recognize non-frontal expressions. Experimental results on the BU-4DFE database show that the proposed method achieves a high recognition accuracy of 86.87% for non-frontal facial expressions within a range of head rotation angle of up to 52%, outperforming existing methods. We also present a quantitative analysis of the components contributing to the performance gain through tests on the BU-4DFE and Multi-PIE datasets.

关键词： facial expression recognition non-frontal head pose depth spatial-temporal convolutional neural network

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Relectrode: A reconfigurable electrode for multi-purpose sensing based on microfluidics 21

Relectrode: A reconfigurable electrode for multi-purpose sen...

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2021 CHI Conference on human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021

作者： Sun, Wei Chen, Yanjun Zhan, Simon Han, Teng State Key Laboratory of Computer Science Beijing Key Lab of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences Beijing China

ISBN: (纸本)9781450380966

In this paper, we propose a reconfgurable electrode, RElectrode, using a microfuidic technique that can change the geometry and material properties of the electrode to satisfy the needs for sensing a variety of diferent types of user input through touch/touchless gestures, pressure, temperature, and distinguish between diferent types of objects or liquids. Unlike the existing approaches, which depend on the specifc-shaped electrode for particular sensing (e.g., coil for inductive sensing), RElectrode enables capacity, inductance, resistance/pressure, temperature, pH sensings all in a single package. We demonstrate the design and fabrication of the microfuidic structure of our RElectrode, evaluate its sensing performance through several studies, and provide some unique applications. RElectrode demonstrates technical feasibility and application values of integrating physical and biochemical properties of microfuidics into novel sensing interfaces. © 2021 ACM.

关键词： Electrodes

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The discovery of user related rare sequential patterns of topics in the Internet document stream 14

The discovery of user related rare sequential patterns of to...

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29th Annual ACM Symposium on Applied Computing, SAC 2014

作者： Hu, Zhongyi Wang, Hongan Zhu, Jiaqi Beijing Key Lab. of Human-Computer Interaction Institute of Software Chinese Academy of Sciences China

ISBN: (纸本)9781450324694

On the Internet, plain text documents created and viewed by users constitute ever changing document streams. Lots of the literature is devoted to topic modeling, while the sequential patterns of topics in document streams are ignored. In this paper, we deal with the problem of mining user related rare sequential patterns of topics in the Internet document streams, which can be used in many fields, such as real-time user behavioral monitoring on the Internet. We propose an approach to discover rare patterns based on the temporal and probabilistic information of topics. Experiments show that the proposed approach can discover user related rare patterns of topic effectively. Copyright 2014 ACM.

关键词： Data mining

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